{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QJb3sp4ZCF_O"
   },
   "source": [
    "# Exploratory Data Analysis\n",
    "\n",
    "Notebook supporting the [**Do we know our data, as good as we know our tools** talk](https://devoxxuk19.confinabox.com/talk/VEM-8021/Do_we_know_our_data_as_good_as_we_know_our_tools%3F) at [Devoxx UK 2019](http://twitter.com/@DevoxxUK).\n",
    "\n",
    "The contents of the notebook is inspired by many sources.\n",
    "\n",
    "### High-level steps covered:\n",
    "\n",
    "- Know the domain knowledge [DEMO - WALKTHRU]\n",
    "- Start with basics: get a feeling of the data [DEMO - WALKTHRU]\n",
    "- Check descriptive statistics [DEMO - WALKTHRU]\n",
    "- Plot distribution of features [DEMO - WALKTHRU]\n",
    "- Check correlations between features, with target column [DEMO - WALKTHRU]\n",
    "- Find issues (missing values, duplicated rows)\n",
    "\n",
    "Steps suggested by [Machine Learning Master: Understand Your Machine Learning Data With Descriptive Statistics in Python](https://machinelearningmastery.com/understand-machine-learning-data-descriptive-statistics-python/):\n",
    "- Peek at Your data\n",
    "- Dimensions of Your Data\n",
    "- Data Type For Each Attribute\n",
    "- Descriptive Statistics\n",
    "- Class Distribution (Classification Only)\n",
    "- Correlation Between Attributes\n",
    "- Skew of Univariate Distributions\n",
    "\n",
    "### Resources \n",
    "\n",
    "- [Helpful Python Code Snippets for Data Exploration in Pandas](https://medium.com/@msalmon00/helpful-python-code-snippets-for-data-exploration-in-pandas-b7c5aed5ecb9)\n",
    "- [The Ultimate Python Seaborn Tutorial: Gotta Catch ‘Em All](https://elitedatascience.com/python-seaborn-tutorial)\n",
    "- [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/)\n",
    "- [Notebook on Boston Housing dataset](https://towardsdatascience.com/linear-regression-on-boston-housing-dataset-f409b7e4a155)\n",
    "- **[Useful cheatsheets](https://github.com/neomatrix369/awesome-ai-ml-dl/blob/master/README-details.md#cheatsheets)**\n",
    "\n",
    "#### Visualisation:\n",
    "\n",
    "- [Fundamentals of Data Visualization](https://serialmentor.com/dataviz/)\n",
    "- [Visualize Machine Learning Data in Python With Pandas](https://machinelearningmastery.com/visualize-machine-learning-data-python-pandas/)\n",
    "- [Python Data Science Notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)\n",
    "\n",
    "#### Notebooks exploring the ML workflow (start-to-finish):\n",
    "\n",
    "- [Learn Machine Learning in a Weekend: Day 1: Regression](https://colab.research.google.com/drive/19uoDyGAxJ0zCwPT6cNb1xkYOfySNZChV#scrollTo=P8BmebTwGIhS)\n",
    "- [Learn Machine Learning in a Weekend: Day 2: Classification](https://colab.research.google.com/drive/1i-fOhU87wWrzgnTV0o54MQyHmRVJK0qt#scrollTo=cy6gO2H7oL3E)\n",
    "\n",
    "\n",
    "Please refer to the [Slides](http://bit.ly/do-we-know-our-data) for the step here after."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "qIhcY8dYE6QZ"
   },
   "source": [
    "### Domain knowledge"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pMktiylmHncM"
   },
   "source": [
    "Ask all the questions you should ask with regards to the domain and related domains or sub-domains.\n",
    "\n",
    "It is a good idea to know the **why** part of the action, why are we doing what we are doing with the data, see the [five whys](https://en.wikipedia.org/wiki/5_Whys).\n",
    "\n",
    "Some ideas (of course, please come up with your own as well):\n",
    "\n",
    "- We want to solve a problem in the end, with ML, and have good results. If we don’t understand our data, we might not be able to train a model because of incoherent or missing data, or have poor results because we have misleading (unbalanced, highly correlated, too many useless features) data. Thus we need to find out if there are incoherent/missing/misleading data\n",
    "- Black box: if anything wrong, if we don’t understand our data, we won’t be able to correct it\n",
    "- If you don’t have domain knowledge, you risk wasting time on finding the root causes of issues. \n",
    "- When I work with someone, I want to get to know that person to get the best out of your relationship\n",
    "- Know the nature / boundaries / source of the data\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aOTleqDMGK1M"
   },
   "source": [
    "### Start with basics: get a feeling of the data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mFimn8EVi_rK"
   },
   "source": [
    "#### Load Your Data [DEMO - WALKTHRU]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  boston_housing_dataset.zip\n",
      "  inflating: column.header           \n",
      "  inflating: housing-unclean.csv     \n",
      "  inflating: housing.csv             \n",
      "  inflating: housing.names           \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100   617    0   617    0     0   1952      0 --:--:-- --:--:-- --:--:--  1958\n",
      "100 27820  100 27820    0     0  26394      0  0:00:01  0:00:01 --:--:--  249k\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "if [[ ! -s boston_housing_dataset.zip ]]; then\n",
    "    curl -O -L https://github.com/neomatrix369/awesome-ai-ml-dl/releases/download/v0.1/boston_housing_dataset.zip\n",
    "fi\n",
    "\n",
    "unzip -o boston_housing_dataset.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 967
    },
    "colab_type": "code",
    "id": "GrREe3x_jC9k",
    "outputId": "488158bb-1e69-4559-da50-99aff7d5c312"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Names and descriptions of the fields of the Boston Housing dataset can be found at\n",
      "https://github.com/jbrownlee/Datasets/blob/master/housing.names\n",
      "\n",
      "1. Title: Boston Housing Data\n",
      "\n",
      "2. Sources:\n",
      "   (a) Origin:  This dataset was taken from the StatLib library which is\n",
      "                maintained at Carnegie Mellon University.\n",
      "   (b) Creator:  Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the \n",
      "                 demand for clean air', J. Environ. Economics & Management,\n",
      "                 vol.5, 81-102, 1978.\n",
      "   (c) Date: July 7, 1993\n",
      "\n",
      "3. Past Usage:\n",
      "   -   Used in Belsley, Kuh & Welsch, 'Regression diagnostics ...', Wiley, \n",
      "       1980.   N.B. Various transformations are used in the table on\n",
      "       pages 244-261.\n",
      "    -  Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning.\n",
      "       In Proceedings on the Tenth International Conference of Machine \n",
      "       Learning, 236-243, University of Massachusetts, Amherst. Morgan\n",
      "       Kaufmann.\n",
      "\n",
      "4. Relevant Information:\n",
      "\n",
      "   Concerns housing values in suburbs of Boston.\n",
      "\n",
      "5. Number of Instances: 506\n",
      "\n",
      "6. Number of Attributes: 13 continuous attributes (including \"class\"\n",
      "                         attribute \"MEDV\"), 1 binary-valued attribute.\n",
      "\n",
      "7. Attribute Information:\n",
      "\n",
      "    1. CRIM      per capita crime rate by town\n",
      "    2. ZN        proportion of residential land zoned for lots over \n",
      "                 25,000 sq.ft.\n",
      "    3. INDUS     proportion of non-retail business acres per town\n",
      "    4. CHAS      Charles River dummy variable (= 1 if tract bounds \n",
      "                 river; 0 otherwise)\n",
      "    5. NOX       nitric oxides concentration (parts per 10 million)\n",
      "    6. RM        average number of rooms per dwelling\n",
      "    7. AGE       proportion of owner-occupied units built prior to 1940\n",
      "    8. DIS       weighted distances to five Boston employment centres\n",
      "    9. RAD       index of accessibility to radial highways\n",
      "    10. TAX      full-value property-tax rate per $10,000\n",
      "    11. PTRATIO  pupil-teacher ratio by town\n",
      "    12. B        1000(Bk - 0.63)^2 where Bk is the proportion of blacks \n",
      "                 by town\n",
      "    13. LSTAT    % lower status of the population\n",
      "    14. MEDV     Median value of owner-occupied homes in $1000's\n",
      "\n",
      "8. Missing Attribute Values:  None.\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "\n",
    "sns.set()\n",
    "\n",
    "names = [line.strip() for line in open(\"column.header\", 'r')]\n",
    "data = pd.read_csv(\"housing-unclean.csv\", names=names)\n",
    "\n",
    "print(\"Names and descriptions of the fields of the Boston Housing dataset can be found at\")\n",
    "print(\"https://github.com/jbrownlee/Datasets/blob/master/housing.names\")\n",
    "print(\"\")\n",
    "!cat housing.names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Mm5EsDitJXgQ"
   },
   "source": [
    "####  Get familiar with columns [DEMO - WALKTHRU]\n",
    "Go through the dataset description. Have some thoughts about which features might be related, what meaning they have, what impact they might have on target variable.\n",
    ">>\n",
    "- Medv is our price that we will try to predict\n",
    "- Some information about type of area (residential / industrial), former has probably a positive impact to price contrary to latter.\n",
    "- Those features about criminality, nitric oxides (pollution?), LSTAT (social class?) should have a negative impact.\n",
    "- etc..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Mm5EsDitJXgQ"
   },
   "source": [
    "####  Dimensions of Your Data [DEMO - WALKTHRU]\n",
    "Have a very good handle on how much data you have, both in terms of rows and columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 121
    },
    "colab_type": "code",
    "id": "WjnQpQCFJq4G",
    "outputId": "4359fa84-6c99-439c-a8eb-9ebcbe31527d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(rows, columms) =  (606, 14)\n"
     ]
    }
   ],
   "source": [
    "shape = data.shape\n",
    "print(\"(rows, columms) = \", shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Mm5EsDitJXgQ"
   },
   "source": [
    "Rows: \n",
    "-       too few rows mean you might not have enough data for your algoritms to train\n",
    "-       too many rows mean your training process will take long\n",
    "\n",
    "Columns / features:\n",
    "-       too few columns/features again will have an impact on generalising or usefulness of the model\n",
    "-       too many columns/featurs could cause training performance to suffer, and does not mean better accuracy\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "OH3OVpoBJRtl"
   },
   "source": [
    "#### Peek at Your Data [DEMO - WALKTHRU]\n",
    "Looking at the raw data can reveal insights that you cannot get any other way.\n",
    "\n",
    "Subsets of data from the head or tail of the dataset can be helpful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 449
    },
    "colab_type": "code",
    "id": "D8ZA1ghXGNAS",
    "outputId": "5b9bc6a3-2302-409e-8683-dd7171650bfd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      crim    zn  indus  chas    nox     rm    age     dis  rad    tax  \\\n",
      "0  0.00632  18.0   2.31   0.0  0.538  6.575   65.2  4.0900  1.0  296.0   \n",
      "1  0.02731   0.0   7.07   0.0  0.469  6.421   78.9  4.9671  2.0  242.0   \n",
      "2  0.02729   0.0   7.07   0.0  0.469  7.185   61.1  4.9671  2.0  242.0   \n",
      "3  0.03237   0.0   2.18   0.0  0.458  6.998   45.8  6.0622  3.0  222.0   \n",
      "4  0.06905   0.0   2.18   0.0  0.458  7.147   54.2  6.0622  3.0  222.0   \n",
      "5  0.02985   0.0   2.18   0.0  0.458  6.430   58.7  6.0622  3.0  222.0   \n",
      "6  0.08829  12.5   7.87   0.0  0.524  6.012   66.6  5.5605  5.0  311.0   \n",
      "7  0.14455  12.5   7.87   0.0  0.524  6.172   96.1  5.9505  5.0  311.0   \n",
      "8  0.21124  12.5   7.87   0.0  0.524  5.631  100.0  6.0821  5.0  311.0   \n",
      "9  0.17004  12.5   7.87   0.0  0.524  6.004   85.9  6.5921  5.0  311.0   \n",
      "\n",
      "   ptratio       b  lstat  medv  \n",
      "0     15.3  396.90   4.98  24.0  \n",
      "1     17.8  396.90   9.14  21.6  \n",
      "2     17.8  392.83   4.03  34.7  \n",
      "3     18.7  394.63   2.94  33.4  \n",
      "4     18.7  396.90   5.33  36.2  \n",
      "5     18.7  394.12   5.21  28.7  \n",
      "6     15.2  395.60  12.43  22.9  \n",
      "7     15.2  396.90  19.15  27.1  \n",
      "8     15.2  386.63  29.93  16.5  \n",
      "9     15.2  386.71  17.10  18.9  \n",
      "\n",
      "The first column lists the row number, which is handy for referencing a specific observation.\n"
     ]
    }
   ],
   "source": [
    "peek = data.head(10)\n",
    "print(peek)\n",
    "print()\n",
    "print(\"The first column lists the row number, which is handy for referencing a specific observation.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SEPARsYEJrnn"
   },
   "source": [
    "#### Data Type For Each Attribute\n",
    "\n",
    "It's important to know the column attributes, since string values may need to be converted to floating point values or integers to represent categorical or ordinal values. If all of them are numbers they will still need to be standardised or normalised.\n",
    "\n",
    "_Best to list all the attributes of the dataset._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 276
    },
    "colab_type": "code",
    "id": "icXl0KwkK7tD",
    "outputId": "1f71680a-67ba-458a-801b-06aa2597df48"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crim       float64\n",
      "zn         float64\n",
      "indus      float64\n",
      "chas       float64\n",
      "nox        float64\n",
      "rm         float64\n",
      "age        float64\n",
      "dis        float64\n",
      "rad        float64\n",
      "tax        float64\n",
      "ptratio    float64\n",
      "b          float64\n",
      "lstat      float64\n",
      "medv       float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "types = data.dtypes\n",
    "print(types)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SEPARsYEJrnn"
   },
   "source": [
    "> We have only numeric data, and should not have missing data (with NaN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "gceJJYXTt5Y9"
   },
   "source": [
    "#### Other attributes of the data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 259
    },
    "colab_type": "code",
    "id": "ZUKegv0nt8bD",
    "outputId": "96510943-7e23-4ea8-9cdf-27ecdf92bb29"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Names of columns Index(['crim', 'zn', 'indus', 'chas', 'nox', 'rm', 'age', 'dis', 'rad', 'tax',\n",
      "       'ptratio', 'b', 'lstat', 'medv'],\n",
      "      dtype='object')\n",
      "\n",
      "Overview of values as an array [[6.3200e-03 1.8000e+01 2.3100e+00 ... 3.9690e+02 4.9800e+00 2.4000e+01]\n",
      " [2.7310e-02 0.0000e+00 7.0700e+00 ... 3.9690e+02 9.1400e+00 2.1600e+01]\n",
      " [2.7290e-02 0.0000e+00 7.0700e+00 ... 3.9283e+02 4.0300e+00 3.4700e+01]\n",
      " ...\n",
      " [3.3147e-01 0.0000e+00 6.2000e+00 ... 3.7895e+02 3.9500e+00 4.8300e+01]\n",
      " [5.3720e-02 0.0000e+00 1.3920e+01 ... 3.9285e+02 7.3900e+00 2.7100e+01]\n",
      " [4.4620e-02 2.5000e+01 4.8600e+00 ... 3.9563e+02 7.2200e+00 2.3900e+01]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Names of columns\", data.columns)   # column names (which is “an index”)\n",
    "print()\n",
    "print(\"Overview of values as an array\", data.values)    # underlying numpy array — df are stored as numpy arrays for effeciencies.\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kP4yEElUGNhi"
   },
   "source": [
    "### Check descriptive statistics [DEMO - WALKTHRU]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0_xLQ4EMLJxn"
   },
   "source": [
    "Descriptive statistics can give you great insight into the shape of each attribute.\n",
    "\n",
    " -  Count\n",
    " -  Mean\n",
    " -  Standard Devaition\n",
    " -  Minimum Value\n",
    " -  25th Percentile\n",
    " -  50th Percentile (Median)\n",
    " -  75th Percentile\n",
    " -  Maximum Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 340
    },
    "colab_type": "code",
    "id": "VTwnUrMVLBss",
    "outputId": "b953f349-ddcf-48fa-dc77-19ff03a1034e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "It is worth taking some time and reviewing observations from the results.\n",
      "This might include the presence of “NA” values for missing data or surprising distributions for attributes.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>b</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>554.000</td>\n",
       "      <td>560.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>555.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>587.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>571.000</td>\n",
       "      <td>589.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>606.000</td>\n",
       "      <td>606.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.480</td>\n",
       "      <td>11.763</td>\n",
       "      <td>11.155</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.554</td>\n",
       "      <td>6.290</td>\n",
       "      <td>68.535</td>\n",
       "      <td>3.774</td>\n",
       "      <td>9.378</td>\n",
       "      <td>407.353</td>\n",
       "      <td>18.453</td>\n",
       "      <td>358.054</td>\n",
       "      <td>12.594</td>\n",
       "      <td>22.737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.325</td>\n",
       "      <td>23.839</td>\n",
       "      <td>6.844</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.115</td>\n",
       "      <td>0.736</td>\n",
       "      <td>28.365</td>\n",
       "      <td>2.096</td>\n",
       "      <td>8.617</td>\n",
       "      <td>167.878</td>\n",
       "      <td>2.176</td>\n",
       "      <td>87.908</td>\n",
       "      <td>7.148</td>\n",
       "      <td>9.516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.460</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.385</td>\n",
       "      <td>3.561</td>\n",
       "      <td>2.900</td>\n",
       "      <td>1.130</td>\n",
       "      <td>1.000</td>\n",
       "      <td>187.000</td>\n",
       "      <td>12.600</td>\n",
       "      <td>0.320</td>\n",
       "      <td>1.730</td>\n",
       "      <td>5.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.080</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5.190</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.449</td>\n",
       "      <td>5.879</td>\n",
       "      <td>43.100</td>\n",
       "      <td>2.100</td>\n",
       "      <td>4.000</td>\n",
       "      <td>280.000</td>\n",
       "      <td>17.400</td>\n",
       "      <td>374.835</td>\n",
       "      <td>6.905</td>\n",
       "      <td>16.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.254</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9.690</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.208</td>\n",
       "      <td>77.800</td>\n",
       "      <td>3.191</td>\n",
       "      <td>5.000</td>\n",
       "      <td>330.000</td>\n",
       "      <td>19.000</td>\n",
       "      <td>391.440</td>\n",
       "      <td>11.395</td>\n",
       "      <td>21.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.520</td>\n",
       "      <td>13.750</td>\n",
       "      <td>18.100</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.624</td>\n",
       "      <td>6.630</td>\n",
       "      <td>94.100</td>\n",
       "      <td>5.118</td>\n",
       "      <td>24.000</td>\n",
       "      <td>666.000</td>\n",
       "      <td>20.200</td>\n",
       "      <td>396.295</td>\n",
       "      <td>16.955</td>\n",
       "      <td>25.975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>88.976</td>\n",
       "      <td>100.000</td>\n",
       "      <td>27.740</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.871</td>\n",
       "      <td>8.780</td>\n",
       "      <td>100.000</td>\n",
       "      <td>12.127</td>\n",
       "      <td>24.000</td>\n",
       "      <td>711.000</td>\n",
       "      <td>22.000</td>\n",
       "      <td>396.900</td>\n",
       "      <td>37.970</td>\n",
       "      <td>50.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          crim       zn    indus     chas      nox       rm      age      dis      rad      tax  \\\n",
       "count  554.000  560.000  606.000  555.000  606.000  606.000  587.000  606.000  571.000  589.000   \n",
       "mean     3.480   11.763   11.155    0.070    0.554    6.290   68.535    3.774    9.378  407.353   \n",
       "std      8.325   23.839    6.844    0.256    0.115    0.736   28.365    2.096    8.617  167.878   \n",
       "min      0.006    0.000    0.460    0.000    0.385    3.561    2.900    1.130    1.000  187.000   \n",
       "25%      0.080    0.000    5.190    0.000    0.449    5.879   43.100    2.100    4.000  280.000   \n",
       "50%      0.254    0.000    9.690    0.000    0.538    6.208   77.800    3.191    5.000  330.000   \n",
       "75%      3.520   13.750   18.100    0.000    0.624    6.630   94.100    5.118   24.000  666.000   \n",
       "max     88.976  100.000   27.740    1.000    0.871    8.780  100.000   12.127   24.000  711.000   \n",
       "\n",
       "       ptratio        b    lstat     medv  \n",
       "count  606.000  606.000  606.000  606.000  \n",
       "mean    18.453  358.054   12.594   22.737  \n",
       "std      2.176   87.908    7.148    9.516  \n",
       "min     12.600    0.320    1.730    5.000  \n",
       "25%     17.400  374.835    6.905   16.800  \n",
       "50%     19.000  391.440   11.395   21.200  \n",
       "75%     20.200  396.295   16.955   25.975  \n",
       "max     22.000  396.900   37.970   50.000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.width', 100)\n",
    "pd.set_option('precision', 3)\n",
    "print()\n",
    "print(\"It is worth taking some time and reviewing observations from the results.\")\n",
    "print(\"This might include the presence of “NA” values for missing data or surprising distributions for attributes.\")\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0_xLQ4EMLJxn"
   },
   "source": [
    ">>\n",
    "- crim zn have a negatively skewed distribution while b has positively skewed distribution\n",
    "- crim zn age  are indeed percentages from 0 to 100\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "deGhLNUXGP4l"
   },
   "source": [
    "### Plot distribution of features [DEMO - WALKTHRU]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 879
    },
    "colab_type": "code",
    "id": "ywZiOeaxMLPi",
    "outputId": "05a31b9b-a357-415c-cbb0-11e1ec26a568"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jeremie/.local/lib/python3.6/site-packages/numpy/lib/histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "/home/jeremie/.local/lib/python3.6/site-packages/numpy/lib/histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_index=1\n",
    "max_plots=4\n",
    "for column in data.columns: \n",
    "    axes = plt.subplot(4, max_plots, plot_index)\n",
    "    axes.set_title('Distribution of '+ column)\n",
    "    axes.figure.set_figheight(15)\n",
    "    axes.figure.set_figwidth(15)\n",
    "    axes.figure.set_tight_layout(False)\n",
    "    plt.hist(data[column],bins=20)\n",
    "    plot_index=plot_index+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">>\n",
    "- the gaps in rad, tax are surprising. are they related ? far away castles ?\n",
    "- confirmations on distributions observed previously\n",
    "- most suburbs have no criminality, that's reassuring!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VT1bz5R_Jzrf"
   },
   "source": [
    "#### Class Distribution (Classification Only)\n",
    "On classification problems you need to know how balanced the class values are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>b</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.006</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.090</td>\n",
       "      <td>1.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.967</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.967</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.032</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.062</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.069</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.062</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    crim    zn  indus  chas    nox     rm   age    dis  rad    tax  ptratio       b  lstat  medv\n",
       "0  0.006  18.0   2.31   0.0  0.538  6.575  65.2  4.090  1.0  296.0     15.3  396.90   4.98  24.0\n",
       "1  0.027   0.0   7.07   0.0  0.469  6.421  78.9  4.967  2.0  242.0     17.8  396.90   9.14  21.6\n",
       "2  0.027   0.0   7.07   0.0  0.469  7.185  61.1  4.967  2.0  242.0     17.8  392.83   4.03  34.7\n",
       "3  0.032   0.0   2.18   0.0  0.458  6.998  45.8  6.062  3.0  222.0     18.7  394.63   2.94  33.4\n",
       "4  0.069   0.0   2.18   0.0  0.458  7.147  54.2  6.062  3.0  222.0     18.7  396.90   5.33  36.2"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 315
    },
    "colab_type": "code",
    "id": "xHnP9jgUhIOT",
    "outputId": "ec16639d-48b8-4ea8-d4be-954b55393ed4"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "We see a nice clustering of instances into two groups.\n",
      "One group between 'rad' index range of 1 and 8, and a second group at 24.\n",
      "From the map it appears that the houses bounded by the river may not have immediate access to the radial highways.\n",
      "This is an interesting subject for further analysis.\n"
     ]
    }
   ],
   "source": [
    "class_counts = pd.value_counts(data[\"rad\"])\n",
    "# print(class_counts)\n",
    "plt.hist(data[\"rad\"], bins=25)\n",
    "plt.title('Index of accessibility to radial highways')\n",
    "plt.show()\n",
    "\n",
    "print()\n",
    "print(\"We see a nice clustering of instances into two groups.\")\n",
    "print(\"One group between 'rad' index range of 1 and 8, and a second group at 24.\")\n",
    "print(\"From the map it appears that the houses bounded by the river may not have immediate access to the radial highways.\")\n",
    "print(\"This is an interesting subject for further analysis.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Cj7QdCNBCMgv"
   },
   "source": [
    "#### Histogram for numeric data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 545
    },
    "colab_type": "code",
    "id": "dlP3QegQK2Vx",
    "outputId": "dad6b6d5-eb59-4e95-cf65-b2a17838b4b5"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can plot a histogram in a slightly different way \n",
    "plt.hist(data[\"medv\"], bins = 40)\n",
    "plt.title('Housing price distribution, $K')\n",
    "plt.show()\n",
    "\n",
    "# and the same for the boxplot\n",
    "plt.boxplot(data[\"medv\"])\n",
    "plt.title('Box plot for housing price.')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-nVr8U6BCUzN"
   },
   "source": [
    "#### Bar chart for categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "pYYVUcw3LpCQ",
    "outputId": "ca090c63-bc36-459e-f158-bb2757b4f93c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "515\n",
      "0.0    516\n",
      "1.0     39\n",
      "Name: chas, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(data[data[\"chas\"] == 0].count()[0])\n",
    "\n",
    "class_counts = pd.value_counts(data[\"chas\"])\n",
    "print(class_counts)\n",
    "labels=[\"Not bounded by Charles River \\n (0 = otherwise)\", \"Bounded by Charles River \\n (1 = track bounds)\", ]\n",
    "plt.bar(labels, class_counts)\n",
    "plt.title('Number of houses')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "J80xth2b3aYU"
   },
   "source": [
    "#### Box whisker / violin plots for category data vs numeric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 3708
    },
    "colab_type": "code",
    "id": "6In-5FowMQft",
    "outputId": "b22a84c9-3daf-4c47-f0a1-af9714e806c2"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAbkAAAELCAYAAABEVvhWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAGiBJREFUeJzt3Xu0XmV94PHvOQkmkRwQDgdtgBC15ielKRpqoR0Eb12OVcbrODIlFBirQQbWtMwswZGKtjJZCGq5KLHWEYmlI3UG5Y9Ch0EmRkovVlwGy4+MEAgXITkRTSgJJifzx95HDof35Lz3yz7fz1pZ73mffXl+2ed9zu99nr33s4f27duHJElVNNzrACRJ6hSTnCSpskxykqTKMslJkirLJCdJqiyTnCSpskxybRIR10bExW3a19KI2BkR88r3d0TE+9ux73J/fx0Rv9eu/TVQ759ExLaI+HGH9n9JRKzrxL4lDab5vQ5gEETEZuDFwB5gL/BD4CvAFzJzAiAzVzewr/dn5m0zrZOZDwGLW4l5Sn2XAL+cmadP2f9b2rHvBuNYClwAHJ2ZT3S7fklzkz25+p2amSPA0cAa4MPAn7e7koio6hePpcB4vQmuwsdBUhcNOePJ7Gr1viLiN4C7gF/LzI0R8WXg4cz8aEQcBnwZOAmYAO4BTgGuA34X2E3RI/wE8DXgAeD9wMeAzcAZZdkBmbknIu4A/hZ4I/BK4FvAWZm5PSJeB6zLzCOnx0vRU/8mMFTW+aPMPK7c37rM/GJEDAMfAX4fWATcApyXmT+NiGVlHGcCfwy8EPhMZn5yhuN0MHAV8BbgX4A/Ay4F3gDcDCwoy/8qM8+ctu3rgHXl9n8A/G/gfOB64ITy//IdYHVmPlxu89LyOK8sfxcJvGhqr1XS3GZPrkmZ+ffAw8Brayy+oFw2RjHM+RFgX2auAh6i6BUuzszLpmxzCnAM8OYZqjwDOBv4JYph0yvriPEWiiTzP8r6jqux2pnlv9cDL6MYJr162jonAUGRZP8oIo6ZocqrgIPL/ZxSxnxW+eXgLcCjZRxnzrD9S4BDKXrLH6D4fP738v1S4Olpsf0F8F3gMIok3PXzjJL6m0NCrXmU4o/ydD+nSEZHZ+b/A75dx74uycynACKi1vLrM3Njufxi4O42XTzyu8CnM/P+ct8XARsj4qwp63w8M58Gvh8R3weOA/556k7Ki2TeB7wqM3cAOyLiCmAV9Q/rTgAfy8zd5funga9PqeOTFL3YyXN8rwHeVK6/PiJubuD/LWkOMMm15ghge43yTwGXAH9TJqwvZOaaWfa1pYHlDwIHUPRgWrWk3N/Ufc+n6IFOmno15L9Q+6KYw8qYpu/riAZi2ZqZuybfRMQLgc8A/xo4pCweKRPqEuAnk18MptR3VAP1Sao4hyubFBGvofgDvmH6sszckZkXZObLgH8D/GFEvLFcPNNJ0NlOjk79472Uore4DXiK4lzZZFzzKIZJ693voxTDgVP3vQd4fJbtpttWxjR9X480sI/psV5AMUx6QmYeBJxclg8BjwGHRMSB0+qTpF8wyTUoIg6KiLcBf0lx8cYPaqzztoj45YgYAn5KcZHJRLn4cYpzVo06PSJ+pezdfILi4o29wH3Awoh4a0QcAHyU4gKPSY8Dy8oLTGq5AfiDiHhpRCzm2XN4exoJrozla8AnI2IkIo4G/pDiYpJmjVAMWT4ZEYdSXJgzWd+DwD8CH4+IF0TEScCpLdQlqYJMcvW7OSJ2UAwb/lfg08BZM6z7CuA2YCfFVZGfy8xvlcv+G/DRiHgyIv5zA/VfT3El4Y+BhRRXHpKZPwU+BHyRotf0FMVFL5NuLF/HI+Kfauz3S+W+11NcSbkLOK+BuKY6r6z/fooe7l+U+2/WZymu+NxGcfXkLdOW/3uKKy+3UyTAr7RQl6QK8hYCSVJl2ZOTJFWWSU6SVFneQiD1kYgYpThH+nLgGWAT8MHM3BoR+4Af8OxFTKtqXfgk6VkmOam/7AMuy8w7ACLiUxRzpf6HcvlvZebOHsUmDZx+TXILKGazeIzi8ntp0MyjmPXmHyjmDa1LZm4H7phSdBdwThvisU1p0DXVpvo1yb2G+qbCkvrda6kxYUA9ynsbz6GYZHvSHeUTGv6aYiq4ehu7bUpV0VCb6tck99jkD+PjjsxMNzq62ONSQz8dl+HhIQ455ECY8lluwlUU91pOTkq9NDO3RMRBFOftLqa4+b8ercQh9ZOGPsv9muR+MZwyMeF9fLV4XGrrw+PS1NBgRFxOManAqVMezLulfP1ZRHyRYkaZhuIYH9/Zj8eoMsbGRti6dUevw6ik4eEhRkcXQ4NtylsIpD4TEZcCxwPvmByOjIhDImJR+fN84D3A3b2LUhoM/dqTk+akiDgWuIhiTtI7y6dYPABcBqwtbyM4ALiTYrhS0n6Y5KQ+kpn3UDxloZZf62YsUhU4XClJqiyTnCSpskxykqTKMslJkirLC0+kOowctIiFC57bXHbt3sOOnz3do4jUSed9dj1P7dpTc9n/ve58dow/1ND+RkaXcsrvXVlz2YEL53PVfzq54RhVH5OcVIeFC+Zz6gXfeE7ZzVe8HW/7raandu3hSxe+ofbCCzfOuF0zN4Ofveb2htZXY+pKcuXsC+8GlgErMnPjtOUfAy6ZuiwiTgTWAouAzcDpmflEuwKXJGk29Z6Tuwk4GXhw+oKIWAmcOHVZObHsOuDczFwOrKd4XIgkSV1TV5LLzA2T8+ZNFRELgGt4/qNAjgd2ZebkTNHXAu9tJVBJkhrV6tWVnwDWZebmaeVLmdKzy8xtwHBEHNpifZIk1a3pC08i4jeBXwcubF84zzc2NtLJ3Q8sj0tt3T4u/h6k/tbK1ZWnAMcAD5STyB4J3BoRZwEPAUdPrhgRhwET5VOPG+JjK57Px3nU1snjMlMym6m+KY8FkdRDTQ9XZuaazFySmcsycxnwMPDmzPwb4LvAoog4qVx9NXBjy9FKktSAupJcRFwZEQ9T9NZui4h79rd++ZDHVcDnI2ITRa+vo8OakiRNV9dwZWaeD5w/yzrLpr2/E1jRdGSSJLXIuSslSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZXVygTNA23koEUsXPDc//6u3XvY8bOnexSRJKnd5mySW7hgPqde8I3nlN18xdtxbn9Jqg6HKyVJlWWSkyRVlklOklRZc/acXCO8SEWSBpNJrg5epCJJg8nhSklSZZnkJEmVZZKTJFWW5+SkPhIRo8D1wMuBZ4BNwAczc2tEnAisBRYBm4HTM/OJXsUqDYK6klxEXA68G1gGrMjMjftrjOU2NkipcfuAyzLzDoCI+BSwJiJ+H1gHnJmZGyLio8Aa4OyeRSoNgHqHK28CTgYenFI22RgjM1cAP6JodETEMEWDPDczlwPrJ5dJmllmbp9McKW7gKOB44FdmbmhLL8WeG+Xw5MGTl1JLjM3ZOaWaWUzNUawQUotK78sngN8E1jKlC+ZmbkNGI6IQ3sUnjQQ2nJOblpjhBoNMiKGI+LQzNzejjqlOeAqYCdwNfDOduxwdHRxO3YzJ4yNjXRtu2br0uzadeHJ1MbYVt3+5TdSXy8/mDaK2vr589KI8jz4K4BTM3MiIh7i2ZESIuIwYKLRL43j4zuZmNjX3mArauvWxqd7GBsbaWq7ZraZa4aHh5r6ktZykpveGMvitjRI6Nwvf6Y/TrXqa2Tdbmi2IVVdJ49Lo5+BZhskQERcSjHk/9bM3F0WfxdYFBEnlacBVgM3NlWBNIe0dJ/clMb4jimNEaY0yPK9DVKqQ0QcC1wELAHujIi7I+J/lV8gVwGfj4hNwCnAhT0MVRoI9d5CcCXwLuAlwG0RMU5xIclFwH0UjRHggcx8Zzm8sgpYGxELKW8h6ED8UqVk5j3A0AzL7gRWdDciabDVleQy83zg/BqLajbGchsbpCSpp5zWS5JUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVdb82VaIiMuBdwPLgBWZubEsXw5cB4wC48AZmblptmWSJHVLPT25m4CTgQenlV8LXJOZy4FrgLV1LpMkqStmTXKZuSEzt0wti4jDgZXADWXRDcDKiBjb37L2hS1J0uxmHa6cwVHAI5m5FyAz90bEo2X50H6WbW20orGxkSZDbE4j9XU7tn6pu5/18+dFUvc1m+S6ZuvWHR3Z70x/nGrV18i63TA2NtKzuvtZJ49Lo5+B4eEhRkcXdyQWSfVr9urKLcARETEPoHxdUpbvb5kkSV3TVJLLzCeAu4HTyqLTgO9l5tb9LWs1WEmSGjFrkouIKyPiYeBI4LaIuKdctBo4LyLuA84r31PHMkmSumLWc3KZeT5wfo3ye4ETZthmxmWSJHWLM55IkirLJCdJqiyTnCSpskxykqTK6vubwaW5Zj+Tom8GdpX/AD6cmbf2IERpYJjkpP5zE/CnwLdrLHvPZNKTNDuTnNRnMnMDQET0OhRp4JnkpMHy1YgYAjYAH8nMJ3sdkNTPTHLS4HhtZm6JiAXAZ4GrgdMb2YGTRtev2SdMNLOdT7PoHJOcNCAmn+uYmbsj4nPANxvdx/j4TiYm9rU9tipq5okWzT4Jw6eKzK7ZJ3t4C4E0ACLiwIg4uPx5CHgfxUTokvbDnpzUZyLiSuBdwEsoJkUfB04Fvl4+umoe8EPgQ72LUhoMJjmpz8w0KTrw6m7HIg06hyslSZVlkpMkVZZJTpJUWSY5SVJlmeQkSZVlkpMkVZZJTpJUWS3fJxcRbwP+GBgq/308M/9nRCwHrgNGgXHgjMzc1Gp9kiTVq6WeXDm90PXAqsx8FbAKuC4ihoFrgWsyczlwDbC21WAlSWpEO4YrJ4CDy59fBDwGHAasBG4oy28AVkbEWBvqkySpLi0NV2bmvoh4L/CNiHgKGAF+BzgKeCQz95br7Y2IR8vyrY3U0e1HUDRSXy8fj+GjOWrr58+LpO5rKclFxHzgIuDtmfmdiPhXwNcohi3bolOPoJjpj1Ot+hpZtxuafZxH1XXyuDT6GWj2sSCS2qvV4cpXAUsy8zsA5etTwC7giHLGdMrXJcCWFuuTJKlurSa5h4EjIyIAIuIY4MXAJopnXZ1Wrnca8L3MbGioUpKkVrSU5DLzx8A5wF9FxPeBvwTOzsztwGrgvIi4DzivfC9JUte0fJ9cZn4V+GqN8nuBE1rdvyRJzXLGE0lSZZnkJEmVZZKTJFWWSU6SVFkmOUlSZZnkJEmVZZKTJFWWSU6SVFkmOUlSZZnkJEmVZZKTJFWWSU6SVFkmOUlSZZnkJEmVZZKTJFWWSU6SVFkmOUlSZZnkJEmVNb/XAUh6VkRcDrwbWAasyMyNZfly4DpgFBgHzsjMTb2KUxoULSe5iFgIfAZ4E7AL+NvM/ICNUmrKTcCfAt+eVn4tcE1mrouI04G1wBu6HZw0aNoxXHkZRXJbnpkrgIvL8slGuRy4hqJRStqPzNyQmVumlkXE4cBK4Iay6AZgZUSMdTs+adC0lOQiYjFwBnBxZu4DyMzHbZRSWx0FPJKZewHK10fLckn70epw5csphiI/FhGvB3YCHwWeZlqjjIjJRrm1xTolNWl0dHGvQxgYY2MjXduu2bo0u1aT3DzgZcD3MvO/RMQJwM3Av205slK3f/mN1NfLD6aNorZ+/ry0YAtwRETMK78wzgOWlOUNGR/fycTEvrYHWEVbt+5oeJuxsZGmtmtmm7lmeHioqS9prSa5h4A9lMOSmfl3EbGNoifXlkbZqV/+TH+catXXyLrd0GxDqrpOHpdGPwPNNshaMvOJiLgbOA1YV75+LzMdFZFm0dI5uczcBnwL+G34xWXOhwP3AZONEmyUUl0i4sqIeBg4ErgtIu4pF60GzouI+4DzyveSZtGO++RWA1+KiCuAnwOrMvPJiFgNXBcRfwT8hOICFUn7kZnnA+fXKL8XOKH7EUmDreUkl5n3A6+rUW6jlCT1lNN6SZIqyyQnSaosk5wkqbJMcpKkyjLJSZIqyyQnSaosk5wkqbJMcpKkyjLJSZIqyyQnSaosk5wkqbJMcpKkyjLJSZIqyyQnSaosk5wkqbJMcpKkyjLJSZIqyyQnSaosk5wkqbJMcpKkyprfrh1FxMeAS4AVmbkxIk4E1gKLgM3A6Zn5RLvqkyRpNm3pyUXESuBE4MHy/TCwDjg3M5cD64E17airGSMHLWJsbOQ5/yRJ1ddyTy4iFgDXAKcBd5TFxwO7MnND+f5ait7c2a3W14yFC+Zz6gXfeE7ZzVe8vRehSJK6qB09uU8A6zJz85SypZS9OoDM3AYMR8ShbahPkqS6tNSTi4jfBH4duLA94Txft4cWG6mvl8OeDrnW1s+fF0nd1+pw5SnAMcADEQFwJHArcCVw9ORKEXEYMJGZ2xutYOvWHS2G2Ngfolr1zbR9O2JrxtjYSM/q7medPC6NfgaGh4cYHV3ckVgk1a+l4crMXJOZSzJzWWYuAx4G3gx8ClgUESeVq64GbmwpUkmSGtSR++QycwJYBXw+IjZR9Pg6NqQpSVItbbtPDqDszU3+fCewop37lySpEc54IkmqLJOcJKmyTHKSpMoyyUmSKqutF55I6qyI2AzsKv8BfDgzb+1ZQFKfM8lJg+c9mbmx10FIg8DhSklSZdmTkwbPVyNiCNgAfCQzn+x1QFK/MslJg+W1mbmlfMTVZ4GrgdPr3dj5NOuz4Fc3cO7tt3SprsWMjfnor04xyUkDJDO3lK+7I+JzwDcb2X58fCcTE/s6EluV7N54El+68A0Nb9fMJOFnr7ndCdfr0Oyk556TkwZERBwYEQeXPw8B7wPu7m1UUn+zJ9ekZ36+93mPX9m1ew87fvZ0XduPHLSIhQuef/gb2YfmnBcDX4+IecA84IfAh3obktTfKpXkZkocnfCCA+Zx6gXfeE7ZzVe8nXoHHRYumP+87Rvdh+aWzLwfeHWv45AGSaWS3P4ShyRp7vGcnCSpskxykqTKMslJkiqrUufkJKldzl5ze1fqOXChf4Y7yaMrSdM0cyM4FImx2W3VGQOb5Lp5u4AkaTC1lCUiYhS4Hng58AywCfhgZm6NiBOBtcAiYDNwemY+0Vq4z6p1u4C3CkiSpmr1wpN9wGWZGZm5AvgRsCYihoF1wLmZuRxYD6xpsS5JkhrSUpLLzO2ZeceUoruAo4HjgV2ZuaEsvxZ4byt1SZLUqLbdQlD23s6hmBV9KfDg5LLM3AYMR8Sh7apPkqTZtPPKjauAnRTPt3pnu3Y6fRLkTmu1vnbEW88+un1cBsWgfV4kdVZbklxEXA68Ajg1Myci4iGKYcvJ5YcBE5m5vdF9z/ScpU79calVX711PfPzvbzggHnPK6/1ZIH97XO2Z0s188yquaCTx2Wm39dM9TX77CtJ7dVykouISynOwb01M3eXxd8FFkXESeV5udXAja3W1e9qPZkAfLKAJPVKq7cQHAtcBNwH3BkRAA9k5jsjYhWwNiIWUt5C0GKskiQ1pKUkl5n3AEMzLLsTWNHK/iVJaoUTNEuSKsskJ0mqLJOcJKmyTHKSpMoyyUmSKsskJ0mqLJOcJKmyTHKSpMoyyUmSKsskJ0mqLJOcJKmyTHKSpMoyyUmSKqudTwaXpMo7+eQTuPfef55x+eGffn7ZK195DOvX/10Ho9JMTHKS1ID9JatOPp1ezXG4UpJUWSY5SVJlmeQkSZXlOTlpgETEcuA6YBQYB87IzE29jUrqX/bkpMFyLXBNZi4HrgHW9jgeqa91tCfnt06pfSLicGAl8Ntl0Q3A1RExlplbexeZ1L863ZPzW6fUPkcBj2TmXoDy9dGyXFINHevJtfitc97kD8PDQzOudPghi+oqa2Tdmeqrd/uZ6q+130bWbWaduaiTx6WRz8uU8nk1V+i+eQCjo4t7HUfljY2N9DqEqmuoTQ3t27evI1FExPHAVzLz2CllPwROz8x/mmXzk4BvdyQwqbteC2xox47KL473AaOZuTci5lGcBnhFHV8cbVOqiobaVL9eXfkPFP+Rx4C9PY5FasY84JcoPsttkZlPRMTdwGnAuvL1e3Wej7NNadA11aY62ZNr5VunpBoi4pUUF3MdAvyE4mKu7G1UUv/qWE+uxW+dkmrIzHuBE3odhzQoOtaTA791SpJ6q6NJTpKkXnLGE0lSZZnkJEmVZZKTJFWWSU6SVFl9eTO4EzsXIuJy4N3AMmBFZm4sy+f08YmIUeB64OXAM8Am4IOZuTUiTqSYI3URsJlihp0nehWrBBARXwb+MTOv7nUsc02/9uSc2LlwE3Ay8OC08rl+fPYBl2VmZOYK4EfAmogYprgn89zy2KwH1vQwTlVURPRlB0HP13e/KB8n8qzM3AAQEb8o8/hAZm4H7phSdBdwDnA8sGvyuFF8GdgMnN3N+FRNEbEP+DjwVuCWiPga8DngQGAh8IXM/Gy57hHAVyimodoMTPQiZvVnT87Hieyfx2eKsvd2DvBNYClTer2ZuQ0YjohDexSequfpzHxNZl5MkbzelJkrgd8APhARx5TrXQmsz8xfAf4jcEpPolVfJjmpEVcBOwHPdagbrpvy8wuBP4+IHwDfAZYAx5XLXg98ESAz7wf+TzeD1LP6McltAY4oJ3SmfF1Slsvj8wvlhTmvAP5dZk4ADwFHT1l+GDBRDm9K7bBzys+XAj8GXp2ZxwF/TzFsqT7Sd0muvBJucmJncGLn5/D4FCLiUopzcO/IzN1l8XeBRRFxUvl+NXBjL+LTnPAiYEtm7omIX6V4lNGk24GzACLipcAbexCf6NO5K53YuRARVwLvAl4CbAPGM/PYuX58IuJYYCPFo5yeLosfyMx3RsRvUVxtupBnbyF4vCeBqlLKC09GMnNn+f7VFLeyTFB8FkeAGzLzy9MuPHmgXOdWbyHovr5McpIktUPfDVdKktQuJjlJUmWZ5CRJlWWSkyRVlklOklRZJjlJUmWZ5CRJlWWSkyRV1v8HrVNrgya2r2EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAbkAAAELCAYAAABEVvhWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3XuYXFWZ7/FvdyJJJM3FTkfkGgXyM0CUAyp4BKKIMih4w4PmSCJkvIAcco6XeQQGxMvI5EHUOUAUPMqIBFFQJ8iZETh5ADFcHC/gGC4vAQkEMNBpQBKGBJPO+WOvguqiqrvrXrXz+zxPnnStfVnv3l3Vb6211167Z8uWLZiZmeVRb7sDMDMzaxYnOTMzyy0nOTMzyy0nOTMzyy0nOTMzyy0nOTMzyy0nuTFIukjSWQ3a1+6S1kuakF7fJOljjdh32t8vJH20Ufurot5/kLRW0ppW111JI39vZta9erbm++QkrQJeCWwCNgN3Az8AvhMRwzXs62MRsayKbW4ClkTEd6upK237RWCviDi+2m0bSdLuQAB7RMQTNWz/feCRiDizjhhOIDv3h9S6DzPLJ7fk4JiI6AP2ABYBnwe+1+hKJE1s9D47xO7AUC0JbjxyfN7MrAXckitpfUl6E3A78LqIWFHc0pA0Dfg+cAgwDNwFzAEuBT4CbCRrEX4ZuBJ4EPgYcDawCpifyl4WEZtSS+424O3Aa4EbgRMj4klJbyVr5e1aGi8wEfg50JPqfCAiXl/cMpTUC5wBfByYAlwLnBoRf5E0I8VxAvAV4OXANyPiqxXO0/bABcBRwH8C/wc4BzgcuAaYlMp/EhEnlGz7VmAJ8C3gM8B64O8j4nJJnwAWA1uA54EbI+KYdJzfTudUwLbA59KxTAdWp338i6RZwB3Ay4DngE0RsUNpC1HSx8m+wLwCWA6cFBGPlTteM8sPt+RKRMS/A48Ah5ZZ/Nm0bICsm/MMYEtEzAMeJmsVTo2Ic4u2mQPMAo6sUOV8YAHwKrJu0/PHEeO1ZEnmx6m+15dZ7YT0723Aa4CpwIUl6xxClkTeDnwhJYxyLgC2T/uZk2I+MX05OAp4LMVxQoXtdwKmAbsAHwW+I0kR8R3gcuDctP0xRdvMBd4N7BARm4AHyH4n2wNfApZIelVE3AOcBNyW9rFDaeWSDgf+ETiO7Dw/BPyoQqxmliPuCirvMbJv/KX+SvZHco+IuB/41Tj29cWIeBZAUrnll0XEirT8LODOBg0e+QjwjYj4U9r36cAKSScWrfOliHgO+IOkPwCvB+4p3kkaJPNhYP+IWAesk/R1YB7VdeueFREbgV9K+leyhPOVUdY/PyJWF15ExFVFy36cjudNwNXjqPsjwCUR8ft0TKcDT0maERGrqjgGM+sybsmVtwvwZJnyrwH3A9dL+pOk08axr9VVLH+IrNtt2riiHN3OaX/F+55I1gItKB4N+Z9krb1S01JMpfvapYpYniok+qLtdx5jmxHnTdJ8SXdKelrS08B+jP88jTgXEbEeGKK6YzCzLuQkV0LSG8n++C0vXRYR6yLisxHxGuA9wGckvT0trnRxc6yLnrsV/bw7WWtxLfAs2bWyQlwTyLpJx7vfx8gG0xTvexPw+BjblVqbYird16NV7GNHSduWbF+4HjbmeZO0B9l1wP8B9KcuyRVk1yRH20fBiHORYumnumMwsy7kJJdI2k7S0WTXapZExB/LrHO0pL0k9QB/IRtkUrjV4HGya1bVOl7SPpJeTjZg5ScRsRm4D5gs6d2SXgacSTbAo+BxYEYaYFLOFcCnJb1a0lRevIa3qZrgUixXAl+V1JcSzmfIBpNU40uStpF0KHA0UOh+HM9525YskQ0CpC7X/YqWPw7sKmmbCttfAZwoaX9Jk8jOxa/dVWmWf05ycI2kdaQRe8A3gBMrrLs3sIxshOBtwLci4sa07B+BM1N32ueqqP8yshGba4DJwEKAiPgL8Cngu2QtjmfJBr0UFJLEkKTfl9nvJWnfN5ONpNwAnFpFXMVOTfX/iayF+8O0//FaAzxF1qK6nGxk471p2feAfdJ5W1pu44i4G/g62Tl/HJgN3FK0yg1kI13XSFpbZvtlwFnAT4E/A3uSXWc0s5zbqm8hsOYrdyuEmVmruCVnZma55SRnZma55e5KMzPLLbfkzMwstzp1xpNJwBvJRsJtbnMsZrWYQDY7zm/I5hdtN3+mrNvV9Jnq1CT3RsY3ZZZZpzuUMhMLtIE/U5YXVX2mOjXJ/RngqaeeZXh45DXD/v6pDA2tb0tQ1XKszdENsfb29rDjjttCei93gIqfKWucbnhvdqtaP1OdmuQ2AwwPbyn7geymD6ljbY4uirVTugZH/UxZ4/j8Nl1VnykPPDEzs9xykjMzs9xykjMzs9zq1GtyZlslSf1kE2vvCTwPrAQ+CewIXMyLT5D/DfCp9NBbM6vALTmzzrIFODciFBGzgQeARWQJ7zMR8VrgdWTPGqzmaRdmWyW35Mw6SEQ8CdxUVHQ7cHJ69t2qtM6wpH8HZrU6PrNu45acWYdKD8Q9Gfh5SfkUYEFpuZm9lFty1rX6tpvC5Ekj38IbNm5i3TO5uUx1AdkDei8sFEiaSPb0+hsiouok198/tXHRbaX2228/7rrrrqq22XfffVmxYkWTIrLROMlZ15o8aSLHfPbqEWXXfP29rGtTPI0k6TyyJ9EfExHDqWwC2ZPVnyI9Qb5aQ0PrfbNynW688baKyxYsuoFLTju87LLBwTy8M9unt7enpi9pYya59GE7FpgBzI6IFal8MvBN4AhgA3BbRHwiLZsJXAr0A0PA/IhYWXV0ZlshSecABwLvjoiNqawX+D7ZbA9/GxHOVGbjMJ5rckuBw4CHSsrPJUtuM9MosLOKll0ELI6ImcBisqHPZjYGSfsCpwM7A7dKulPSvwBHAccDs4HfpfLFbQzVrCuM2ZKLiOUAkl4okzQVmA/sWvhGGRGPp2XTgQOAd6TVrwAulDQQEYMNjd4sZyLiLqCnwuJK5WZWQa3X5PYk64Y8W9LbyC6On5kS4m7AoxGxGSAiNkt6LJVXleQq9b8ODPTVGHbrOdbmGC3WbjoOM2uuWpPcBOA1wB0R8XeSDgKukbRX40Irf5F8YKCvay7gOtbmKMRaKZl1wnHUepHczBqr1vvkHiabWugKgIj4NbAWmAmsBnZJI8EKI8J2TuVmZmYtU1OSi4i1wI2k625pNOV04P6IeAK4E5ibVp9L1uLz9TgzM2upMZOcpPMlPQLsCiyTVLgL8iTgDEl/JLs5dV5EPF207FRJ9wGnptdmZmYtNZ7RlQspc+NpRPwJeGuFbe4FDqo3ODMzs3p47kozM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8utMR+aCiDpPOBYYAYwOyJWlCw/G/hi8TJJBwMXA1OAVcDxEfFEowI3MzMby3hbckuBw4CHShdIOgA4uHiZpF5gCXBKRMwEbgYW1R2tmZlZFcaV5CJieUSsLi2XNAlYDJxcsuhAYENELE+vLwKOqydQMzOzatV7Te7LwJKIWFVSvjtFLbuIWAv0SnpFnfWZmZmN27iuyZUj6c3AG4DTGhfOSP39U8uWDwz0NavKhnOszTFarN10HGbWXDUnOWAOMAt4UBLArsB1kk4EHgb2KKwoaRowHBFPVlPB0NB6hoe3jCgbGOhjcHBdHWG3jmNtjkKslZJZJxxHb29PxS9pZtY6NXdXRsSiiNg5ImZExAzgEeDIiLge+B0wRdIhafWTgKvqjtbMzKwK40pyks6X9AhZa22ZpLtGWz8ihoF5wLclrSRr9TWtW9PMzKyccXVXRsRCYOEY68woeX0rMLvmyMzMzOrkGU/MzCy3nOTMzCy36hldaWYNJqkfuAzYE3geWAl8MiIGPVVe65z6Tzfz7IZNNW27YNENVa2/7eSJXPC/DqupLhubk5xZZ9kCnBsRNwFI+hqwSNLHyabKOyEilks6k2yqvAVtizTHnt2wiUtOO7zq7Wq5FafapGjVcXelWQeJiCcLCS65neyeU0+VZ1YDJzmzDpUmOj8Z+DmeKs+sJu6uNOtcFwDrgQuB9zdih56FZfxqnR6ulu08FV3zOMmZdaD0DMe9gWMiYlhS06bKs/JqmR6u1unxOmEquk5X61R57q406zCSziG7Bve+iNiYij1VnlkN3JIz6yCS9gVOB+4Dbk2Tnz8YEe+XNA+4WNJk0i0EbQvUrEs4yZl1kIi4C+ipsMxT5ZlVyd2VZmaWW05yZmaWW05yZmaWW05yZmaWW05yZmaWW+MaXZluTD0WmAHMjogVo82WnrbxjOlmZtZW423JLQUOo2juPF6cLV0RMRt4gGxW9MKce0uAUyJiJnBzYZmZmVmrjKslV5j5PN2YWih7EripaLXbySaThfIzpq/CjwUxM7MWasg1uZLZ0sEzppuZWQdo1IwnxbOlN0ylyTi7acZux9oco8XaTcdhZs1Vd5IrnS09FTdtxvRaZ/luB8faHIVYKyWzTjiOWmdMN7PGqqu7ssJs6eAZ083MrAOM9xaC84EPADsByyQNAcdRYbb09Pwrz5huZmZtNd7RlQuBhWUWlZ0tPW3jGdPNzKytPOOJmZnllpOcmZnllh+aamZWYtJ+yznlhmtbVNdU4PCW1LU1cpIzMyuxccUhXHJa9YmnlltxFiy6AY6uuiobJ3dXmplZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbjnJmZlZbo05QbOk84BjgRnA7IhYkcpnApcC/cAQMD8iVo61zMzMrFXG05JbChwGPFRSfhGwOCJmAouBi8e5zMzMrCXGTHIRsTwiVheXSZoOHABckYquAA6QNDDassaFbWZmNrZanye3G/BoRGwGiIjNkh5L5T2jLBtsQMxmuTXK5YGjga+Qfb56gC9FxM/aFadZt+joh6b2908tWz4w0NfiSGrnWJtjtFi76TjKWAr8b+BXhQJJPcBlwKERsULS64BbJC2NiOE2xWnWFWpNcquBXSRNSC21CcDOqbxnlGVVGRpaz/DwlhFltTx5t10ca3MUYq2UzDrhOHp7eyp+SRtNRCwHkFS6aBjYPv28A/BnJzizsdV0C0FEPAHcCcxNRXOBOyJicLRl9QZrtjWKiC3AccDVkh4ia+3Nb29UZt1hPLcQnA98ANgJWCZpKCL2BU4CLpX0BeApRn7oRltmZlWQNBE4HXhvRNwi6S3AlZL2iYj11eyrltbl1qrWbu9atuvyLvaONmaSi4iFwMIy5fcCB1XYpuIyM6va/sDOEXELQEp0zwKzgN9Us6NylwCsvFq6vWvt9u+ELvZOV+slAM94Ytb5HgF2VbpQJ2kW8ErggbZGZdYFOnp0pdnWptLlAUknAz+RVBhssiAinmxboGZdwknOrIOMcnngcuDy1kdk1t3cXWlmZrnlJGdmZrnlJGdmZrnlJGdmZrnlJGdmZrnlJGdmZrnlJGdmZrnl++TMzMpYsOiGltSz7WT/GW4mn10zsxKXnHZ4TdstWHRDzdtac7i70szMcstJzszMcstJzszMcstJzszMcstJzszMcqvu0ZWSjga+AvSkf1+KiJ9JmglcCvQDQ8D8iFhZb31mZmbjVVdLTlIPcBkwLyL2B+YBl0rqBS4CFkfETGAxcHG9wZqZmVWjEd2Vw8D26ecdgD8D04ADgCtS+RXAAZIGGlCfmZnZuNTVXRkRWyQdB1wt6VmgD3gXsBvwaERsTuttlvRYKh8c7/77+6eWLR8Y6Ksn7JZyrM0xWqzddBxm1lx1JTlJE4HTgfdGxC2S3gJcSdZtWbehofUMD28ZUTYw0Mfg4LpG7L7pHGtzFGKtlMw64Th6e3sqfkkzs9apt7tyf2DniLgFIP3/LLAB2EXSBID0/87A6jrrMzMzG7d6k9wjwK6SBCBpFvBKYCVwJzA3rTcXuCMixt1VaWZmVq+6klxErAFOBn4i6Q/Aj4AFEfEkcBJwqqT7gFPTazMzs5ap+z65iLgcuLxM+b3AQfXu38zMrFae8cTMzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHLLSc7MzHKr7mm9zKxxJJ0HHAvMAGZHxIpUPhn4JnAE2VM+bouIT7QrTrNu4ZacWWdZChwGPFRSfi5ZcpsZEbOBs1odmFk3ckvOrINExHKA9PQq0s9TgfnArhGxJa33eFsCNOsyTnJmnW9PYAg4W9LbgPXAmYWEaGaVOcmZdb4JwGvIHjz8d5IOAq6RtFdEPFPNjvr7pzYlQHvRwEBfu0OwIk5yZp3vYWATcAVARPxa0lpgJvDbanY0NLSe4eEtjY/QXjA4uK7dIeRSb29PTV/S6k5ylUZ9SZoJXAr0k3W1zI+IlfXWZ7a1iYi1km4E3gFcnz5b04H72xuZWedrxOjKSqO+LgIWR8RMYDFwcQPqMss1SedLegTYFVgm6a606CTgDEl/BH4EzIuIp9sVp1m3qKslV2nUl6TpwAFk3zwh62a5UNJARAzWU6dZnkXEQmBhmfI/AW9teUBmXa7e7sqyo76A54BHI2IzQERslvQYsBvgJGdmZi1Rb5IrO+oL+G91R0blkWDdNHrJsTbHaLF203GYWXPVm+Qqjfp6DthF0oTUipsA7Aysrmbn5UaCDQz0dc3oJcfaHIVYKyWzTjiOWkeCmVlj1TXwJCLWAoVRXxSN+roPuBOYm1adS9bac1elmZm1TCNGV1Ya9XUScKqk+4BT02szM7OWqfs+uUqjviLiXuCgevdvZmZWKz+FwMzMcstJzszMcstJzszMcstJzszMcstJzszMcstJzszMcstJzszMcstJzszMcstPBretQt92U5g8aeTbfcPGTax75rk2RWRmreAkZ1uFyZMmcsxnrx5Rds3X30v7p3I2s2Zyd6WZmeWWk5yZmeWWk5yZmeWWk5yZmeWWk5yZmeWWk5yZmeVWw24hkHQ28EVgdkSskHQwcDEwBVgFHB8RTzSqPjMzs7E0pCUn6QDgYOCh9LoXWAKcEhEzgZuBRY2oq1P0bTeFgYG+Ef/6tpvS7rDMzKxI3S05SZOAxcBc4KZUfCCwISKWp9cXkbXmFtRbX6fwzcVmZp2vES25LwNLImJVUdnupFYdQESsBXolvaIB9ZmZmY1LXS05SW8G3gCc1phwRurvn1q2fGCgrxnVNURpbJ0ca6mBgT6e/+tmtnnZhBHl5crabbTzWs0576bfj5lVr97uyjnALOBBSQC7AtcB5wN7FFaSNA0Yjognq9n50NB6hoe3jCgbGOhjcLD9nYKV/jgWx9YpsY5HIdaBgb6y3bCddBzFsZZTLtZq1m2E3t6eil/SzKx16uqujIhFEbFzRMyIiBnAI8CRwNeAKZIOSaueBFxVV6RmZmZVasp9chExDMwDvi1pJVmLryldmmZmZpU09FE7qTVX+PlWYHYj929mZlYNz3hiZma55YembqXKPSnbIw3NLG+c5LZS5W5mh2wkpbWXpPOAY4EZpGnySpaPmEKv5QGadRF3V5p1nqXAYRRNqFBQOoWemY3OSc6sw0TE8ohYXVpeNIXeya2Pyqw7ubvSGqrctb4NGzex7pnn2hRRrrwwhV6afMHMxuAkZw3liaubo1FT6HkWlubzAK7O4iRn1h3KTqEn6cSIuH68Oyk3VZ41VidNgZcntU6V5yRn1gUiYhFFz2SUtAo42qMrzUbnJGdN9/xfN5ftwvG1uvIknQ98ANgJWCZpKCL2bXNYZl3JSc6abpuXTah4T547dl4qIhYCC8dYZ0ZrojHrbk5yVrNyIynNzDqJ/0JZzSqNpDQz6xS+GdzMzHLLLTkzsyocdthB3HvvPRWXT//GS8te+9pZ3Hzzr5sYlVXiJNelKl0P84hFs+YaLVkNDPT5PrkOU1eSk9QPXAbsCTwPrAQ+GRGDkg4GLgamAKuA4yPiifrCtYLRniLgj5iZWabea3JbgHMjQhExG3gAWCSpF1gCnBIRM4GbKbqR1czMrBXqaslFxJPATUVFt5PNkH4gsCEilqfyi8hacwvqqc/ypdxN4q3sbm13/WbWfA27JpdabycDPwd2p+h5VxGxVlKvpFekxGhW9ibxVna3trt+M2u+Rg48uQBYD1wIvL8RO6w0GWcnz/JdGls7Ym1Gna08jvHUNdo69cbaye8vM6tOQ5KcpPOAvYFjImJY0sPAHkXLpwHD1bbiys2Y3imjlyr9ISyOrRBrM56xNtof4vGcn2r/kJfbZ7OSwVjxF87reH4Hxds0qv7xqHXGdDNrrLqTnKRzyK7BvTsiNqbi3wFTJB2SrsudBFxVb13dys9YMzNrj3pvIdgXOB24D7g1PefqwYh4v6R5wMWSJpNuIagzVjMzs6rUO7ryLqCnwrJbgdn17N/MrBtMn77dS8qeeOKZNkRipTx3pXWUwrD+0n99201pd2hmZRUSXG9vL8uWLaO3t3dEubWXp/WyjuJnz1k36u3tZc2apxkY6GPNmqfZaacdGB4ebndYhltyZmZ1u/LKpaO+tvbJVUvOkxY3R7mZQczsRccd9z7WrHl6xGvrDLlKcp60uDlG60I0MxgeHmannXbg+uuv553vfKe7KjuIuyvNzOpQGEU5PDzMEUcc8UKC8+jKzpCrlpx50mGzdigktE6Zkcle5CSXM5502Kz15sw5mHvuufuF17Nm7cMvf3l7GyOyAndXNlDpPV7gyX7N8q6Q4I488igGBwc58sijuOeeu5kz5+B2h2a4JddQjRig0YzJnM2seQoJ7rLLfsy0aX1cdtmPmTfvQ1x33S/aHZrhJNdxPJmzWff55jcXv+T1Pvu8pk3RWDF3V5qZ1enTnz5l1NfWPk5yZmZ1mDVrH6677hfMm/ch1q5d+0JX5axZ+7Q7NMPdlVsFz1hi1jy//OXtzJlzMNdd9wsGBgYAj67sJE5yXaDeJFXptoJuUnoOnLStkxQSmu+T6zxdm+QqzVOZR3lIUvXyOTCzWnRtlqg0CtHMzKygqUlO0kzgUqAfGALmR8TKZtbZLXydzMys+ZrdkrsIWBwRSyQdD1wMHN7kOruCZ/bvLr5J36w7NS3JSZoOHAC8IxVdAVwoaSAiBsfYfAJAb29P2YWF8uk7TnnJsnJl5fY1depkJpX80dq4cRPr1294ybbl1q22/mas2+7tO7WuSu+berafPGkif/sP148o+96Z7+TZMd6jpPdyBxj1M2WN43PcHLV+pnq2bNnS+GgASQcCP4iIfYvK7gaOj4jfj7H5IcCvmhKYWWsdCixvdxD4M2X5UdVnqlMHnvyG7ED+DGxucyxmtZgAvIrsvdwJ/JmyblfTZ6qZLbnpwH1Af0RsljSBbPDJ3uPorjQzM6tb06b1iogngDuBualoLnCHE5yZmbVK01pyAJJeS3YLwY7AU2S3EETTKjQzMyvS1CRnZmbWTn4KgZmZ5ZaTnJmZ5ZaTnJmZ5ZaTnJmZ5VZH3Awu6TzgWGAGMDsiVkjqBy4D9gSeB1YCnyx3C4Kk7wNHAGtT0VUR8dVWxZrKVwEb0j+Az0fEdWW2fznwz8CBwCbgcxHxf1sVq6QZwNKi1XYAtouIV5TZ/ovAp4DHUtEtEXFKk2Kt+PuWdDDZvKdTgFVks+Y8UWYfLTu3tvVIn4NzIuL5GradAbwzIr5TVPZvwKkR8UDDgrSKOqUltxQ4DHioqGwLcG5EKCJmAw8Ai0bZx6KI2D/9a0qCGyXWgg8WxfCSBJd8DngmIvYCjgG+K2lqq2KNiFVFMe6f1vnhKPv4QdH6TUlwSdnft6ReYAlwSkTMBG6m8vuglefWth5nA9uUWyBprIbCDOATxQUR8S4nuNbpiJZcRCwHkFRc9iRwU9FqtwMntzSwMsrFWqUPAR9N+1op6bfAUcBVDQmwyFixStoG+AhwZKPrrtYov+8DgQ2FYyF7ssUqYEGZ3bTs3Fq+SNoCfBl4L1mPwRkR8VNJi9Mqt0oaBt4K/BNZT4GAPmB/SZen15OA+4EFEfEUsBh4taQ7gfsj4oOp1+fo1LOyF1kvxUDa5xkRcW0rjnlr0SktuVGlb/MnAz8fZbXPSPqjpKWSZrUotFKXS/oPSd+StEOFdXZnZCvwYWC35odW1nuAR8eYMPvD6Ziul/TmVgRV8vsecb4iYi3QK+kl3aul69Lec2vdZ3Pq3XgP8B1J04t6L/5r6s14Or3eH/ibtD7A/4yIN6ReiLuAz6fyU4C707YfLFPn5cAPI+J1wPHAEkkDzTi4rVVXJDngAmA9cGGF5X8P7JXeYD8Drk1zZbbSoRHxeuCNQA+VY+0kC4BLRll+EfDq9AH8GnB1unbWbGP9vs2a4XsAaVam3wMHj7LuTyLi2aLX8yX9TtIfgf9OlgRHJakvrffPqd67yaZCHK1eq1LHJ7k0eGJv4EMRMVxunYh4tLAsIn4ATAV2bV2UEBGr0/8bgW8Bb6mw6sPAHkWvdwdWNze6l5K0CzCH7JtkWRGxJiL+mn7+f2Rx7tfkuEp/3yPOl6RpwHDq3izVEefWtgrrCz9IOpSs5+Fv0hftM4HJ7QrMRuroJCfpHLJrMu9LyaPSersU/Xwk2aNEHm1+hC/Uua2k7dPPPcCHyb6RlXMV8Mm07t5kLb929MF/FPjXiBiqtELJed2f7CJ60+YerfD7/h0wRdIh6fVJVL7G1inn1rrTifDCe+e/kF0XBlgHbD/KdjsAfwGGJE1i5PXiZyptGxHryP5OfDTVOwt4fVG91gAdMfBE0vnAB4CdgGWShoDjgNPJHtdzaxo88WBEvD9tcyfwroh4DLhU0iuBYbI31XsiYlMLYz0G+GnqIp0A3E029L6wTXGsXwO+L+l+smT8ifRmb0msRQ+xPQFYWGabfwO+EBG/Bc5JD7/dTDasf15ErGlSrPtS4fctaR5wsaTJpFsIirZry7m1XJoo6Q7g5WS3rxRuU/k6cIOk58gGnpS6luw9eR/ZbUw3A29Ky/4e8RWOAAAAYUlEQVQDCEkrgHvLXJf7CNl7+9NkA0/m+UktjeUJms1sq5dGV/ZFxPoxV7au0tHdlWZmZvVwS87MzHLLLTkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8stJzkzM8ut/w+6keD25uYKfwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we loop through all the columns\n",
    "for col in data.columns:\n",
    "    # and for each column we create space for one row with 2 charts \n",
    "    f, axes = plt.subplots(1, 2, figsize=(7, 4))\n",
    "    # our first chart is a histogram and we set the title \n",
    "    data[col].hist(bins = 30, ax = axes[0])\n",
    "    axes[0].set_title('Distribution of '+ col)\n",
    "    # our second column is the boxplot \n",
    "    data.boxplot(column = col, ax = axes[1])\n",
    "    # we then use this to command to display the charts\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "sAgs5coRGSQO"
   },
   "source": [
    "### Check correlations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "l4YVL-p43VKq"
   },
   "source": [
    "#### Scatter charts for numeric data [DEMO - WALKTHRU]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 879
    },
    "colab_type": "code",
    "id": "ywZiOeaxMLPi",
    "outputId": "05a31b9b-a357-415c-cbb0-11e1ec26a568"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 13 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_index=1\n",
    "max_plots=4\n",
    "for column in data.columns: \n",
    "  if column != \"medv\":\n",
    "      axes = plt.subplot(4, max_plots, plot_index)\n",
    "      axes.set_title('Distribution of '+ column + \" v/s medv\")\n",
    "      axes.figure.set_figheight(15)\n",
    "      axes.figure.set_figwidth(15)\n",
    "      axes.figure.set_tight_layout(False)\n",
    "      plt.scatter(data[column], data[\"medv\"], marker='o')\n",
    "      plot_index=plot_index+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">>\n",
    "we can already see multiple obvious correlations between each feature and the price.\n",
    "\n",
    ">>\n",
    "some linear:\n",
    "- nb of rooms\n",
    "\n",
    ">>\n",
    "more complex:\n",
    "- criminality \n",
    "- proportion of non retail businesses\n",
    "- percentage of lower status of the population\n",
    "\n",
    ">> \n",
    "some with no correlation:\n",
    "- age: proportion of owner occupied units built prior to 1940\n",
    "- rad: index of accessibility to radial highways\n",
    ">>\n",
    "etc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ck3LgHNHKCf5"
   },
   "source": [
    "#### Correlation Between Attributes [DEMO - WALKTHRU]\n",
    "\n",
    "Correlation refers to the relationship between two variables and how they may or may not change together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1014
    },
    "colab_type": "code",
    "id": "Ps3O65S9hzwn",
    "outputId": "4dfb4962-6f30-43c2-e6cb-483aa365535b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          crim     zn  indus       chas    nox     rm    age    dis        rad    tax  ptratio  \\\n",
      "crim     1.000 -0.202  0.414 -5.020e-02  0.426 -0.231  0.354 -0.382  6.295e-01  0.588    0.292   \n",
      "zn      -0.202  1.000 -0.537 -5.647e-02 -0.517  0.310 -0.574  0.673 -3.151e-01 -0.315   -0.408   \n",
      "indus    0.414 -0.537  1.000  8.199e-02  0.765 -0.399  0.639 -0.710  5.918e-01  0.718    0.390   \n",
      "chas    -0.050 -0.056  0.082  1.000e+00  0.112  0.100  0.109 -0.119  2.582e-04 -0.023   -0.128   \n",
      "nox      0.426 -0.517  0.765  1.124e-01  1.000 -0.319  0.731 -0.771  6.002e-01  0.667    0.192   \n",
      "rm      -0.231  0.310 -0.399  9.996e-02 -0.319  1.000 -0.248  0.206 -2.103e-01 -0.317   -0.377   \n",
      "age      0.354 -0.574  0.639  1.086e-01  0.731 -0.248  1.000 -0.753  4.494e-01  0.500    0.285   \n",
      "dis     -0.382  0.673 -0.710 -1.189e-01 -0.771  0.206 -0.753  1.000 -4.922e-01 -0.536   -0.248   \n",
      "rad      0.629 -0.315  0.592  2.582e-04  0.600 -0.210  0.449 -0.492  1.000e+00  0.912    0.454   \n",
      "tax      0.588 -0.315  0.718 -2.305e-02  0.667 -0.317  0.500 -0.536  9.116e-01  1.000    0.464   \n",
      "ptratio  0.292 -0.408  0.390 -1.283e-01  0.192 -0.377  0.285 -0.248  4.542e-01  0.464    1.000   \n",
      "b       -0.383  0.179 -0.346  5.490e-02 -0.361  0.132 -0.268  0.279 -4.482e-01 -0.437   -0.190   \n",
      "lstat    0.458 -0.411  0.595 -5.133e-02  0.588 -0.615  0.592 -0.486  4.743e-01  0.544    0.389   \n",
      "medv    -0.380  0.350 -0.469  1.861e-01 -0.418  0.714 -0.373  0.232 -3.615e-01 -0.459   -0.515   \n",
      "\n",
      "             b  lstat   medv  \n",
      "crim    -0.383  0.458 -0.380  \n",
      "zn       0.179 -0.411  0.350  \n",
      "indus   -0.346  0.595 -0.469  \n",
      "chas     0.055 -0.051  0.186  \n",
      "nox     -0.361  0.588 -0.418  \n",
      "rm       0.132 -0.615  0.714  \n",
      "age     -0.268  0.592 -0.373  \n",
      "dis      0.279 -0.486  0.232  \n",
      "rad     -0.448  0.474 -0.362  \n",
      "tax     -0.437  0.544 -0.459  \n",
      "ptratio -0.190  0.389 -0.515  \n",
      "b        1.000 -0.350  0.318  \n",
      "lstat   -0.350  1.000 -0.739  \n",
      "medv     0.318 -0.739  1.000  \n",
      "\n",
      "A correlation of -1 or 1 shows a full negative (inverse) or positive (direct) correlation respectively.\n",
      "A value of 0 shows no correlation at all.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f3ec495a7b8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pairwise Pearson correlations\n",
    "pd.set_option('display.width', 100)\n",
    "pd.set_option('precision', 3)\n",
    "correlations = data.corr(method='pearson')\n",
    "print(correlations)\n",
    "print()\n",
    "print(\"A correlation of -1 or 1 shows a full negative (inverse) or positive (direct) correlation respectively.\") \n",
    "print(\"A value of 0 shows no correlation at all.\")\n",
    "\n",
    "# Generate a mask for the upper triangle\n",
    "mask = np.zeros_like(correlations, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Set up the matplotlib figure\n",
    "f, ax = plt.subplots(figsize=(10, 10));\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sns.heatmap(correlations, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5},annot=True)\n",
    "# correlation_matrix = boston.corr().round(2)\n",
    "# annot = True to print the values inside the square\n",
    "# sns.heatmap(correlations, annot=True,mask=mask, cmap=cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The features with high correlations should not be used together in case of some models (linear regression): dis and nox, tax and rad "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kP4yEElUGNhi"
   },
   "source": [
    "### Find issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "l6m_cfK5vGnx"
   },
   "source": [
    "#### Count missing values\n",
    "\n",
    "Count the number of missing values across all the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 276
    },
    "colab_type": "code",
    "id": "v3hUAuKfvIVu",
    "outputId": "c7cc3999-eec1-4ef4-8b15-e3eeea38038e"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZEAAAELCAYAAAAY3LtyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3XmYXGWZ/vFvEnaIBjCKASQoeguIrJFFNvf9x6jIgCDIoqLAOKigAyjLoKIQZ0YJgyjKDm7oiBsMMklgAEUgIMvciBDZZAhJWIIkQpLfH+/poWi7k+7TXUuq7s919dVVp87yPl3V9Zzzvuc8Z8zSpUuJiIioY2y7GxARESuuJJGIiKgtSSQiImpLEomIiNqSRCIiorYkkYiIqC1JJIZN0jmSTm7TtsdI+q6k+ZJ+2442jAZJL5O0QNK4ZcyzVNImTdr+LyUdMILlz5T0+dFs00hJOkHSBe1uR69Zqd0NiJGTNBtYA9jY9lPVtEOA/Wzv3r6WNcXOwFuADfpiXRHZvg9Yq++5pOnABba/3aLtv2OEyx86Wm2JFVuORLrHOOCT7W7EcC1rT3wQGwGzh5pAJGVHKaKJ8g/WPU4FjpZ0hu3HGl+QNBm4F1jZ9rPVtOlUe76SPgx8BPgtcCAwD9gPeBXwz8CqwFG2z21Y7Ysk/SewA3ATsL/tP1XrfjXwDWBbYA7wedvfr147B3iakgx2A/YAruzX3knAmZSjjnnAV2x/S9LBwDRgZUkLgKm2j++3bGMs+wP/LukLwDHV9NWBXwFH2H5c0rnArbanSlofeAA43PY0Sa8AbgBeBKwDnFO1aQlwO7Cb7SX9tn8isI7tIyStDDwGnGH7KEmrA/OBScAL+t4T4ERgF2AHSf8KnGP78GqVb5b0S2AicGHVtr8pMyHpBGBzYFH1N50NvL/6ObKafrDtK6r5p/Pc+78JcDawFfAM8Gvbfy9pDPA1YF9gNeBPwD62b6vexwdsHydpd+AC4F+AzwKLgWNsf7fa1rrV3243wMDlwO62dx4gjl8CP7d9esO0W4ATbV8q6d+A9wEvBP4A/KPtqwdYz+5VfBs0TJsNHGL7SkljgaMpn4kJwK+BQ23Pk7Qa8G3gHZSdsz8A77b9v/23EzkS6Sa/A6YDn6m5/PbArcC6wEXAJcAUYBNKQjld0loN8+9LSTAvAmZRvuCQtCbwn9U6XgzsDZwhabOGZT8IfBEYD1wzQFsuoXyZTwL2BL4k6Y22zwYOBa6zvVb/BNIvlnuAl1Tb+XD18wbg5ZRupL4vqRnA7tXj3arldm14fnWVKD5dtWlitd5jgIFqBjWubwrwcMP6dgRse17jAraPBa6mJIi1GhIIwLur9bwW2At42yAxA7wHOB9YG7iZ8mU9FlgfOAn45iDL/TNwRbXcBpQdAIC3Vm1/FeVLey9g7iDrWK+aZ33gYGCapLWr16YBT1XzHFD9DOZiYJ++J9XnZiPg59WkGyjJbh3KZ+wH1Zf+cB0B/B3lPZ5ESe7TqtcOqGLZkPL/cChlxycGkCTSXb4AHCFpYo1l77X9XduLge9R/oFOsr2o2nv9KyWh9Pm57Zm2FwHHAjtK2pDypTe7Wteztm8GfgR8oGHZ/7D937aX2F7Y2IhqHa8HPmt7oe1ZlL3C/YcRy0O2v1Ft/2lKwvua7XtsLwD+Cdi76uqaAexc7ZnuCny12j6UL5gZ1eNngJcCG9l+xvbVAx0RANcBr6z2vnel7OGvXyXgxvUN1Sm2H6vGUP6L8gU6mKttX14dbf6AkvBOsf0MJTFPljRhgOWeoXxRT6r+5tc0TB8PvBoYY/tO238eZNvPUD4vz9j+BbAAUNVd+X7geNt/sX0HcO4g6wD4MbCVpI2q5/sCl1afM2xfYHtu9d5OpRwlaxnrG8yhwLG2H6jWfQKwZ/WZeIaSPDaxvdj2jbafqLGNnpAk0kVs3wb8DPhcjcUbD9WfrtbXf1rjkcj9DdtdQOl2mkT5Mtpe0mN9P5QvgvUGWnYAk4B5tp9smPYnyh7uUPVf/6RqHY3rWwl4ie0/UvaSt6J0Kf0MeEiSeP6X/qnA3cAVku6RNODfuEpav6uW3bVa/lpKYqqTRB5uePwXnv8e9Nf//Xq02inoe84gyx8NjAF+K+l2SQcB2L6KcsQ2DXhE0lmSXjDItuf2dZX2a+tEyt+68T0Z9P2v3vefU45goRyVXNj3uqTPSLpT0uPVZ+uFlKPh4doI+HHDZ/ROSjfcSyhHc5cDl0h6SNJXq67JGEDGRLrP8ZQxiqkN0/oGodcA+vaoGr/U69iw70G1l70O8BDlC2KG7bcsY9lllY5+CFhH0viGRPIy4MFhtK3/+h+ifGn0eRnwLM996c6gdJutYvtBSTMoXRprU7rq+r7cPg18WtJrgKsk3WD71wNsfwbwRmBrSvfLDEo31OuAmUNsc8vYfpgyNoCknYErJc20fbftrwNfl/Ri4PvAUcBwTu2dQ/lbbwDcVU3bcPDZgdKldbykmZSxmP+q2rYLJeG9Cbjd9hJJ8ykJsL+nKJ93qmXHURJan/uBg2z/9yBtOBE4sRpP/AVlLOfs5bS7J+VIpMvYvpvSHfUPDdPmUL6E95M0rtrTfMUIN/VOSTtLWoXSp3697fspe/KvkvQhSStXP1MkbTrE9t9P2XP/sqTVJL2W0sc+kvP/LwaOlLRxlfC+BHyvYc95BnA4z33BT6+eX9O3Jy/p3ZI2qQabH6fstT5vUL3BDEr32x22/1qt7xBKl+GcQZb5X8p4TctJ+oCkvgHo+ZSEtqR637av9sKfAhYyeMwDqv5+lwInSFqjOulieV2Tv6Ak/ZMo71PfNsdTEtIcYKXqhInBjozuAlaT9K6q/cdRur76nAl8sa/bTNJESXtUj98gaYsq8TxB6d4aVty9JEmkO50ErNlv2kcoe5FzKWfxXDvCbVxEOeqZRzkLaz/4vz32t1K6Ix6idMd8hef/Ay/PPsDkavkfU/rTr1zmEsv2HUoXxUzKGVELKQOrfWZQvqD6ksg1lL3YxqOGV1LOIltAGfc4w/Z/DbK9aylngfUtf0e1zcGOQgD+jdInP1/S14cW1qiZAvymOuPtp8Anbd9D+YL+FiWx/Iny2Tm1xvoPp3Q7PUx5Hy6mnC02oGqM4lLgzZTPWZ/LKWfW3VW1ZyGDdI3Zfhz4BGU87UFKEnygYZZ/o8R6haQngespJ2RAOUr/ISWB3En5fJw/1GB7zZjclCoiWknSV4D1bNe+Yj46R8ZEIqKpqi6sVYDfU456DqZ070UXSBKJiGYbT+nCmkQZ+5kK/EdbWxSjJt1ZERFRWwbWIyKitm7tzlqV0vf6Z8qpmBERsXzjKJUZbmAZZ9A16tYkMoVSiygiIoZvFwaua/c3ujWJ/Blg/vynWLKkd8Z81l13LebOXdDuZrRUL8YMvRl3Ym6+sWPHsPbaa0L1HToU3ZpEFgMsWbK0p5II0HPxQm/GDL0Zd2JumSEPA2RgPSIiaksSiYiI2pJEIiKitiSRiIioLUkkIiJqSxKJiIjakkQiIqK2JJGIiKgtSSQiImrrqCQi6cOSftjudkRExNB0VBKJiIgVS+3aWZKWAscBfwesC3wEeDPwdmBl4AO276zmPQD4RLW9x4GP27akVYBvAG8EHgVublj/H4A9bd9SPT8c2Nb2gXXbHBERo2ukBRgfsz1F0gcot7vc2/Y/SToaOBbYT9IuwF7ArrYXSXoH8B3g9cDHgI2BzSiJZyYwu1r3ucABwKeq5wcCRw6nceuuu9ZIYlshTZw4vt1NaLlejBl6M+7E3HlGmkS+V/2+CVhq+2fV8xuB91WP3wNsCfxGEsAYYO3qtTcA59p+BnhG0gXAztVr51XLHA1sCkxgmPcImTt3QU9V/Zw4cTxz5jzZ7ma0VC/GDL0Zd2JuvrFjxwx753ukSWRh9Xsxz78L1uKGdY8BvmP7C8NZse37JN0OvAPYHTjHdu9khIiIFUArBtYvA/aXtAGApHGStq1euwr4kKSVJK0OfLDfsucAhwD7ULq3IiKigzQ9idieSRkf+amkW4DbgD2ql88C7gPupCSUG/otfinlKOQO2/c1u60RETE8Y5Yu7coeosnAvRkT6X69GDP0ZtyJufkaxkQ25rmTnJa9TDMbFBER3S1JJCIiaksSiYiI2pJEIiKitiSRiIiorSlJRNJSSYNe9ihpQnUl+lDXd0JVZysiIjpIu45EJgBDTiLA8UCSSEREhxlp2ZNlkjQWOJ1SpXcRsMD264FpwARJs4C/2N5J0qeBvas2LaRU+p0laVq1umslLQF2t/1YM9sdERFD09QkQim8+AZgM9tLJPUVXjwM+J3trRrmPc/2VABJbwbOBHawfZikTwA72V7Q5PZGRMQwNDuJ3EMp8X62pKuAny1j3m0lHQOsAywBXjXSjacUfG/oxZihN+NOzJ2nqUnE9uOSNqfUv3oz8BVJ2/Sfrxo0/yHlniM3SZoEPDjS7afsSffrxZihN+NOzM1XpxR8UwfWJU0E1rB9OfA5yl0NXw48AawhqS+JrUZJaPdXzz/Rb1VPAi9sZlsjImL4mn121obAlVX13luBXwLX254HXAj8XtK1tp8AvgDcIOlG4Kl+65kKXCVplqQJTW5zREQMUar4dpEc7veOXow7MTdfqvhGRERLJYlERERtSSIREVFbkkhERNSWJBIREbV1bBJZXiXgiIhov45NIhER0fk6PYkcVV1gaEnvb3djIiLi+To9iSyuKv3+P+AsSS9ud4MiIuI5za7iO1JnA9i2pJuAHYCfDnXhVPHtDb0YM/Rm3Im583R6EhmRlD3pfr0YM/Rm3Im5+Tquiu8oOBBA0iuBrYHr29uciIho1OlHIitJuhlYA/iY7Ufa3aCIiHhOxyYR22Oqhye0sx0RETG4Tu/OioiIDpYkEhERtSWJREREbUkiERFRW5JIRETUliQSERG1jSiJSDpB0io1l50s6aP9pv1C0itG0qaIiGidkR6JHA8MmEQkLe8alMnA85KI7Xfa/uMI2xQRES2y3IsNJS0FTgL2AFYHjrH9I0nTqlmulbQE2B34V+BZQMB4YCtJF1bPVwXuBg6yPR+YBmwsaRZwt+09Jc0G3m37NkmbAN8EJlbrPMb2r0Yn7IiIGA1DvWJ9se2tJImSNK62fZikTwA72V4AUF5mK2A3209Vy37S9qPV6ycDnwU+BxwGnGZ7u0G2eSFwlu2zJW0GzJS0qe05Qw0uVXx7Qy/GDL0Zd2LuPENNIsMpyf7DhgQCsL+kfSndXmsCdy1vY5LGU5LRd6vt3lEdsewAXDbENqeKbw/oxZihN+NOzM3XKVV8F/Q9kLQL8HHg7ba3AI4DVmvCNiMiog2GmkQGK8n+JPDCZSw3AXgcmCtpVeCghteeGGxZ208Cs4ADqu1uCmxJSsFHRHSUoXZnDVaSfSpwlaSnKQPr/f0K2I/ShfUoMBN4XfXarYAl3Qb8j+09+y27L/BNSUdSBtY/NJzxkIiIaL4xS5cue8ygOjtrfN/g+QpiMnBvxkS6Xy/GDL0Zd2JuvoYxkY2B2UNappkNioiI7rbc7qyGm0NFREQ8T45EIiKito69Pe5oyMWGnWvhomd58omn292MiBihrk4iB598BY/MzxdVJ7ps6h701hBpRHdqeXfWSCr/RkREZ2nHmMiglX8jImLF0tLurAEq/34V+CTPJZXP2P61pBcDvwX2tP07SQcAHwF2t/1sK9scERGDa+mRiO3Dqoc72d4KuBzYwfbWwN7AudV8jwAfBi6StAOlFP0+SSAREZ2l3QPrrwAulrQ+8AywnqT1bD9se7qki4BrgPfavr+tLY1RN1pnkq0oZ6SNtl6MOzF3nnYnkYuBT9v+iaSxwF94fpXfrYE5wAbtaFw012iUc+jFUhjQm3En5ubrlFLwy9NY+XcCcG/1+CDK3Q8BqAovrgxsA3xW0latbGRERCxfO5JIX+XfWcA/Aj+pbnT1cmAugKTXAf8AHGD7z5RB9Uuqm1VFRESHaHl3lu0TgRMbJp3f8PiY6vdsShXJvmX+E3h10xsXERHD0u4xkaY6+7i3trsJMYiFi3KiXUQ36OokkvuJREQ0V6r4RkREbV19JJIqvr2hF2OG9sSd6svRX1cnkVTxjRhdqb4c/a0w3VmSzpF0eLvbERERz2lbEpHU1UdBERG9oNVVfJdSrhF5F/ArSd8HzgDWpJQ7Ocv2v1bzrg+cB7yUct3Ikla2NSIilq8dRyJP255i+/OU5PBm29sArwM+KmnTar6vAzNtbwYcDuzWhrZGRMQytKNL6dyGx2sA/y5pS8qRxiRgS+BO4A2U0ifYvkfSr1vd0Ij4W+08G64Xz8Tr9JjbkUQWNDz+EvAw8GHbz0q6gudX8Y2IDtOuC1p78WLaVPFdvgnA/VUCeQ2wS8NrVwEHAkjaGHhTG9oXERHL0O4zpE4Gzpd0MHAXMLPhtU8C50n6IKVc/PTWNy8iIpalpUnE9ph+z28GXjPIvA+So4+IiI7W7u6siIhYgbW7O6upUgo+YnSlhH/019VJJKXgu18vxgy9G3d0nnRnRUREbUkiERFRW5JIRETU1jFjIlVxxvHANcCOtnMjkIiIDtcxSaSP7a3a3YaIiBiatiURSe+j1M5aCPyoYXrfEclfgNOBNwKLgAW2X9+GpkZExCDakkQkvQT4FrCTbUs6eoDZtqRU8t3M9hJJaw93O7nHem/oxZihN+NOzJ2nXUci2wM32Xb1/CzgK/3muQdYGThb0lXAz4a7kVwn0v16MWbozbgTc/OtiFV8B2X7cWBz4BLgtcDtktZrb6siIqJRu5LI9cDWkl5ZPT+k/wySJgJr2L4c+BzwOPDy1jUxIiKWpy1JxPYjwEeByyTdzMA3otoQuFLSLcCtwC8pySciIjpE287Osn0pcGnDpJOr333l4m8Ctm1poyIiYlg6dkwkIiI6X5JIRETUliQSERG1dVzZk9GUiw27x8JFz/LkEymnFtFpujqJHHzyFTwyP1883eCyqXvQW5eZRawY0p0VERG1JYlERERtLenOknQhIGBV4G7gINvzJX0R+HtgLjAdeJPt7aplDgA+UbXxceDjDbW2IiKiA7TqSOSTtrezvQVwO/BZSe8B3k2p1rsj0FcCBUm7AHsBu9reFjgV+E6L2hoREUPUqoH1/SXtC6wCrAncVT3+vu2nACSdC3y+mv89lOTyG0lQrmIfdin46C6DnXnWrWekLU8vxp2YO0/Tk0h1VPFxyr1D5kj6IKVu1rKMAb5j+wvNbl+sOAYqid2L5cGhN+NOzM3XqaXgJ1DGNOZKWhU4qJo+HdhT0hqSxgIfaljmMsrRywYAksZJSh2tiIgO04ok8ivgj5QurBmUworY/ilwOaVC7/XAQ5Rkg+2ZwLHAT6sqvrcBe7SgrRERMQxN786y/QzlDKyBfNH256ojkW8D1zUsdyFwYbPbFxER9bX7ivXzJE0GVgduBL46mis/+7i3jubqoo0WLnq23U2IiAG0NYnYfm8z1597rEdENFeuWI+IiNqSRCIiorYkkYiIqC1JJCIiauuIJCKp3WeJRUREDW378pa0FDgReBfwK0l/BD4IPAa8FngQOAI4DdgEuAHYz3bvnG4VEdHh2n0k8rTtKbb7Ci9OAT5l+9XA08BFlMSyGbAF8Kb2NDMiIgbS7m6kc/s9/2/bD1SPbwZm234MoCp/sglw5VBXnnus94ZejBl6M+7E3HnanUQW9Hu+sOHx4gGeD6u9udiw+/VizNCbcSfm5uvUKr4REdGlkkQiIqK2MUuXdmV3z2Tg3nRndb9ejBl6M+7E3HwN3VkbA7OHtEwzGxQREd0tSSQiImpLEomIiNqSRCIiorYkkYiIqC1JJCIiaksSiYiI2pJEIiKitpbUzqrKvh8LvBdYFzjK9o+q194OfBkYB8wBPmb7bkn7UUrB70ypm3UF8EPbZ7aizRERsXwtuWK9SiJH2D5d0uuB79teX9KLgduB3WzfIelg4KO2t6+WO5tyf5HHgdfY3muIm5wM3DvqgURE9IYhX7Heyiq+l1S/rwcmSVoN2B64xfYd1WvfBc6QNN72k8DhwI3AysC2w91gyp50v16MGXoz7sTcfJ1exXchgO3F1fOhJLD1gLWAVYAXNKldERFRU7sH1q8HtpT06ur5AcDNtp+UtArwPeBo4ATgktyLPSKis7Q1idieA3wIuEjSrcB+1Q/AV4FZti+x/V3KGMfJ7WlpREQMJKXgu0j6jHtHL8admJsvpeAjIqKlkkQiIqK2JJGIiKitq8dE2t2IiIhmWLjoWZ584ulRX2+dMZGuPmX24JOv4JH5o/+Hjohop8um7kGnnGLQku4sSbMlvaYV24qIiNbJmEhERNQ26t1ZknYETgXGV5OOqn7vJelbwEuB02yfXs1/GrAbpbTJo8BBtv9UFWe8CHhJtfyVto8c7fZGRER9o3okImkd4MfA0ba3BLYBbqheXsP2jsDuwCmS+qp8nWJ7SjX/xcBXqun7An+0vYXtLYCTRrOtERExcqN9JLIjcIfta+H/ii3OlwRVFV/bsyXNBzYA/gd4h6TDKIUWG9tzPXCkpFOBGcDlo9zWiIgV1sSJ45c/Uwu08uyshQ2PFwMrSdoI+Bdgiu17Je1E6cLC9nWStgbeQqmv9TnKDaoiInpeM8qhdEIp+OuAzapxESSNk7T2MuZ/AfBX4GFJY4FD+16QtDHwhO1LgE8B21bzREREhxjVL2Xb84D3AV+rqvLeyDJuJmX798APgDuA3/D8CwR3B26SNAv4JXCo7SWj2d6IiBiZrr5iPRcbRkQ3umzqHs3uzhryFetdnUTa3YiIiGZI2ZMWyf1Eul8vxgy9GXdi7kwZqI6IiNqSRCIiorYkkYiIqG1ESUTSLEmr11guVX0jIrrAiAbWbW81Wg2JiIgVz4iSiKSlwHjbCyTNBs6jlCnpX6l3F+CMarEZwJiB1tH4HFgCnAtsDjwD2PZeI2lvRESMrtEeE/mbSr2SVqUUXzyiqsY7E3jZENb1NuAFtjerKvx+bJTbGhERIzTa14kMVKl3FeAvtqdXr31f0llDWNctwKaSpgHTgZ8PtzHDLSTWDTqlsmcr9WLM0JtxJ+bOM9pJ5G8q9Q4y39J+840FkLRa30Tb90jaHHgT8A7gS5K2sL2QIcrFht2vF2OG3ow7MTdfJ1TxHYiB1atxESTtCUxoeP1uYEr1+IN9EyVtACy2/RPgSGAisE4L2hsREUPU9CRiexGwD3BGVdl3d+C+hlk+BXxT0o2URNFnC+A6SbcAvwW+bPuhZrc3IiKGrqsLMKY7q/v1YszQm3En5uarU4AxV6xHRERtSSIREVFbkkhERNSWJBIREbV19U2pcrFhb+jFmKE34+60mJt1h8EVSVcnkdxjPSKa6bKpe9Bb54v9rXRnRUREbUkiERFRW9u7syS9E/hSw6TNgA8AJwK/AXak1Nra2/adrW9hREQMpu1JxPYvgF8ASPoIcCCwiHIfkQNtf0zSscBxwL5ta2hExACaPdjfaScT9Nf2JNJH0tsodbR2AV5DuQnVzdXL1wPvaVfbIiIG08yyJKniO0SStgTOBPaw/Wg1eahl5SMiok3ankQkrQ/8CNjP9l3tbk9ERAxdJ+zdH0IpAT9NUt+0I9vXnIiIGKq2JxHbJ1LOxOpvu4Z5pjc+j4iIztD2JNJMZx/31nY3ISK62MJFz7a7CW3X1UkkN6Xqfr0YM/Rm3L0Y84qg7QPrERGx4urq2+O2uxEREa02ksrCdW6P29XdWaniGxG9ptWVhdvWnSVpO0kXtmv7ERExcm05EpG0ku3fkVpYERErtKYkEUk7AqcCfZXDjgLOAi4B3gj8XtL5wGm2t5M0Gfgd8C3g7cDqlARzKLA98DSlJMrDzWhvRETUM+rdWZLWAX4MHG17S2Ab4Ibq5RfYfp3tgwdYdF3gGttbA2cDvwam2X4tcCNw+Gi3NSIiRqYZRyI7AnfYvhbA9mJgflXS5LxlLLfA9s+rxzcBD9ieVT2/EXhLE9oaEdF1Wlk+vtVjIguW8dqihseLSRXfiIha6l6U2Sml4K8DNqvGRZA0TtLaTdhORES02agnEdvzgPcBX5N0K6UratvR3k5ERLRfV1+xnosNI6LXXDZ1j9HozhryFetdnUTa3YiIiFZL2ZNRlCq+3a8XY4bejDsxd6ZU8Y2IiNqSRCIiorYkkYiIqC1JJCIiaksSiYiI2pJEIiKitiSRiIiorVuvExkH5cKZXpOYe0cvxp2YW7atcUNdpluvWN8ZuLrdjYiIWEHtAlwzlBm7NYmsCkwB/kwpIx8REcs3Dngp5UaCi5YzL9C9SSQiIlogA+sREVFbkkhERNSWJBIREbUliURERG1JIhERUVuSSERE1JYkEhERtXVd2RNJrwLOBdYF5gL72/5De1s1uiSdBryfci/5LWzfVk3v2tglrQucD7wC+CvwB+BjtudI2gH4JrA65b7Q+9l+pF1tHW2SfkK55/USYAFwhO1Z3fx+95F0PHAC1ee8m99rSbOBhdUPwGdtX97pMXfjkciZwDTbrwKmUf743eYnwK7An/pN7+bYlwJftS3bWwB/BE6RNBa4ADisinsmcEob29kMB9je0vbWwGnAd6rp3fx+I2kbYAeqz3mPvNd72t6q+rl8RYi5q5KIpBcD2wAXV5MuBraRNLF9rRp9tq+xfX/jtG6P3fY829MbJl0PbARsCyy03Vfn50xgrxY3r6lsP97w9IXAkm5/vyWtSkmMH2+Y3PXv9QA6PuauSiLAhsCDthcDVL8fqqZ3u56Jvdo7+zjwU+BlNByR2X4UGCtpnTY1rykkfVvSfcAXgQPo/vf7JOAC27MbpvXCe32hpFslnSFpAitAzN2WRKI3fIMyNnB6uxvSKrYPsf0y4Bjg1Ha3p5kk7QhsB5zR7ra02C62t6QUjx3DCvL57rYkcj+wvqRxANXvSdX0btcTsVcnFbwS+HvbS4D7KN1afa+/CFhie16bmthUts8H3gA8QPe+37sBmwL3VoPNGwCXA5vQxe91Xxe17UWUBPp6VoDPd1clkeqMhVnAPtWkfYCbbc9pX6taoxdil/QlSh/x31X/aAA3AqtL2rl6figX+oWcAAAA50lEQVTwg3a0rxkkrSVpw4bn7wHmAV37fts+xfYk25NtT6YkzLdRjsC68r2WtKakF1aPxwB7U97fjv98d10peEmvppz2uDYwn3Lao9vbqtEl6evA+4D1gEeBubY37+bYJW0O3AbcBTxdTb7X9nsl7UQ5M2k1njsF8n/b0tBRJuklwH8Aa1LujTMP+Iztm7r5/W5UHY28uzrFtyvfa0kvB35EuZ/HOOAO4B9s/7nTY+66JBIREa3TVd1ZERHRWkkiERFRW5JIRETUliQSERG1JYlERERtSSIREVFbkkhERNSWJBIREbX9f85acSGXirb0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_rows = data.shape[0]\n",
    "total_rows_without_missing_values = data.count()\n",
    "missing_values_count=(total_rows - total_rows_without_missing_values)\n",
    "\n",
    "plt.barh(data.columns, missing_values_count)\n",
    "plt.title(\"Number of rows with missing values\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Vr0i_CVsxayx"
   },
   "source": [
    "#### Count occurrence of values per column\n",
    "\n",
    "Count the number times each value in a column is occurring across the whole dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "colab_type": "code",
    "id": "d_WR90enxZ4N",
    "outputId": "247b919d-ac56-469f-a1e5-2bfbee48dc20"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Print the count for other columns as well, maybe even plot them on a bar chart / histogram\n"
     ]
    }
   ],
   "source": [
    "plt.hist(data[\"crim\"], bins = 10)\n",
    "plt.title('Criminality distribution, (occurence)')\n",
    "plt.show()\n",
    "\n",
    "print(\"Print the count for other columns as well, maybe even plot them on a bar chart / histogram\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "H6NPZJIOymvv"
   },
   "source": [
    "#### Count number of unique values per column\n",
    "\n",
    "Count the number unique values in a column occurring across the whole dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "AmRnU3S-ymXJ",
    "outputId": "7fbded71-863e-488d-bba3-91544dba4e29"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "46"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.ptratio.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Rca8_2uzzMNM"
   },
   "source": [
    "#### Duplicated rows\n",
    "Get stats on the number of non-unqiue or duplicate rows in a dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 65
    },
    "colab_type": "code",
    "id": "1BfB2BiU7aRH",
    "outputId": "c8834de3-0a64-439b-e1ce-aabec84dd1f6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "% of duplicated rows to total rows in the dataset: 8.25082508250825\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>crim</th>\n",
       "      <th>zn</th>\n",
       "      <th>indus</th>\n",
       "      <th>chas</th>\n",
       "      <th>nox</th>\n",
       "      <th>rm</th>\n",
       "      <th>age</th>\n",
       "      <th>dis</th>\n",
       "      <th>rad</th>\n",
       "      <th>tax</th>\n",
       "      <th>ptratio</th>\n",
       "      <th>b</th>\n",
       "      <th>lstat</th>\n",
       "      <th>medv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>556</th>\n",
       "      <td>0.142</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.547</td>\n",
       "      <td>6.254</td>\n",
       "      <td>84.2</td>\n",
       "      <td>2.256</td>\n",
       "      <td>6.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>388.74</td>\n",
       "      <td>10.45</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>557</th>\n",
       "      <td>0.841</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.599</td>\n",
       "      <td>85.7</td>\n",
       "      <td>4.455</td>\n",
       "      <td>4.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>303.42</td>\n",
       "      <td>16.51</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>558</th>\n",
       "      <td>0.037</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.443</td>\n",
       "      <td>6.968</td>\n",
       "      <td>37.2</td>\n",
       "      <td>5.245</td>\n",
       "      <td>5.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>14.9</td>\n",
       "      <td>392.23</td>\n",
       "      <td>4.59</td>\n",
       "      <td>35.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>559</th>\n",
       "      <td>0.140</td>\n",
       "      <td>22.0</td>\n",
       "      <td>5.86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.431</td>\n",
       "      <td>6.487</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.397</td>\n",
       "      <td>7.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>19.1</td>\n",
       "      <td>396.28</td>\n",
       "      <td>5.90</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560</th>\n",
       "      <td>0.298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.504</td>\n",
       "      <td>7.686</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3.375</td>\n",
       "      <td>8.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>377.51</td>\n",
       "      <td>3.92</td>\n",
       "      <td>46.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>3.321</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.58</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.871</td>\n",
       "      <td>5.403</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.322</td>\n",
       "      <td>5.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>26.82</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562</th>\n",
       "      <td>0.140</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.520</td>\n",
       "      <td>6.167</td>\n",
       "      <td>90.0</td>\n",
       "      <td>2.421</td>\n",
       "      <td>5.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>392.69</td>\n",
       "      <td>12.33</td>\n",
       "      <td>20.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>563</th>\n",
       "      <td>0.053</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.489</td>\n",
       "      <td>7.079</td>\n",
       "      <td>63.1</td>\n",
       "      <td>3.414</td>\n",
       "      <td>2.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.06</td>\n",
       "      <td>5.70</td>\n",
       "      <td>28.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>6.444</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.584</td>\n",
       "      <td>6.425</td>\n",
       "      <td>74.8</td>\n",
       "      <td>2.200</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>97.95</td>\n",
       "      <td>12.03</td>\n",
       "      <td>16.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>565</th>\n",
       "      <td>1.388</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.950</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3.990</td>\n",
       "      <td>4.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>232.60</td>\n",
       "      <td>27.71</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>1.131</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>5.713</td>\n",
       "      <td>94.1</td>\n",
       "      <td>4.233</td>\n",
       "      <td>4.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>360.17</td>\n",
       "      <td>22.60</td>\n",
       "      <td>12.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>0.122</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.445</td>\n",
       "      <td>6.625</td>\n",
       "      <td>57.8</td>\n",
       "      <td>3.495</td>\n",
       "      <td>2.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>357.98</td>\n",
       "      <td>6.65</td>\n",
       "      <td>28.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>568</th>\n",
       "      <td>0.615</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.507</td>\n",
       "      <td>6.618</td>\n",
       "      <td>80.8</td>\n",
       "      <td>3.272</td>\n",
       "      <td>8.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.60</td>\n",
       "      <td>30.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>0.082</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.428</td>\n",
       "      <td>6.481</td>\n",
       "      <td>18.5</td>\n",
       "      <td>6.190</td>\n",
       "      <td>6.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>16.6</td>\n",
       "      <td>379.41</td>\n",
       "      <td>6.36</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.614</td>\n",
       "      <td>6.229</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.951</td>\n",
       "      <td>NaN</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>383.32</td>\n",
       "      <td>13.11</td>\n",
       "      <td>21.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>571</th>\n",
       "      <td>0.956</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.047</td>\n",
       "      <td>88.8</td>\n",
       "      <td>4.453</td>\n",
       "      <td>4.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>306.38</td>\n",
       "      <td>17.28</td>\n",
       "      <td>14.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>572</th>\n",
       "      <td>0.035</td>\n",
       "      <td>95.0</td>\n",
       "      <td>2.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.416</td>\n",
       "      <td>7.853</td>\n",
       "      <td>33.2</td>\n",
       "      <td>5.118</td>\n",
       "      <td>4.0</td>\n",
       "      <td>224.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>392.78</td>\n",
       "      <td>3.81</td>\n",
       "      <td>48.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>573</th>\n",
       "      <td>9.339</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.679</td>\n",
       "      <td>6.380</td>\n",
       "      <td>95.6</td>\n",
       "      <td>1.968</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>60.72</td>\n",
       "      <td>24.08</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>574</th>\n",
       "      <td>0.527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.504</td>\n",
       "      <td>8.725</td>\n",
       "      <td>83.0</td>\n",
       "      <td>2.894</td>\n",
       "      <td>8.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>382.00</td>\n",
       "      <td>4.63</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>575</th>\n",
       "      <td>6.801</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.713</td>\n",
       "      <td>6.081</td>\n",
       "      <td>84.4</td>\n",
       "      <td>2.717</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>14.70</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>0.009</td>\n",
       "      <td>90.0</td>\n",
       "      <td>2.97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.400</td>\n",
       "      <td>7.088</td>\n",
       "      <td>20.8</td>\n",
       "      <td>7.307</td>\n",
       "      <td>1.0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>394.72</td>\n",
       "      <td>7.85</td>\n",
       "      <td>32.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>577</th>\n",
       "      <td>0.088</td>\n",
       "      <td>12.5</td>\n",
       "      <td>7.87</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.524</td>\n",
       "      <td>6.012</td>\n",
       "      <td>66.6</td>\n",
       "      <td>5.561</td>\n",
       "      <td>5.0</td>\n",
       "      <td>311.0</td>\n",
       "      <td>15.2</td>\n",
       "      <td>395.60</td>\n",
       "      <td>12.43</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578</th>\n",
       "      <td>1.519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.58</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.605</td>\n",
       "      <td>8.375</td>\n",
       "      <td>93.9</td>\n",
       "      <td>2.162</td>\n",
       "      <td>5.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>388.45</td>\n",
       "      <td>3.32</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>6.444</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.584</td>\n",
       "      <td>6.425</td>\n",
       "      <td>74.8</td>\n",
       "      <td>2.200</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>97.95</td>\n",
       "      <td>12.03</td>\n",
       "      <td>16.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>580</th>\n",
       "      <td>0.015</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2.01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.435</td>\n",
       "      <td>6.635</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.344</td>\n",
       "      <td>4.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>390.94</td>\n",
       "      <td>5.99</td>\n",
       "      <td>24.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>581</th>\n",
       "      <td>0.009</td>\n",
       "      <td>90.0</td>\n",
       "      <td>2.97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.400</td>\n",
       "      <td>7.088</td>\n",
       "      <td>20.8</td>\n",
       "      <td>7.307</td>\n",
       "      <td>1.0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>394.72</td>\n",
       "      <td>7.85</td>\n",
       "      <td>32.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>1.425</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.58</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.871</td>\n",
       "      <td>6.510</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.766</td>\n",
       "      <td>5.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>364.31</td>\n",
       "      <td>7.39</td>\n",
       "      <td>23.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>0.358</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.20</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.507</td>\n",
       "      <td>6.951</td>\n",
       "      <td>88.5</td>\n",
       "      <td>2.862</td>\n",
       "      <td>8.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>391.70</td>\n",
       "      <td>9.71</td>\n",
       "      <td>26.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>0.030</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3.78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.484</td>\n",
       "      <td>6.874</td>\n",
       "      <td>28.1</td>\n",
       "      <td>6.465</td>\n",
       "      <td>5.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>387.97</td>\n",
       "      <td>4.61</td>\n",
       "      <td>31.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>0.140</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.520</td>\n",
       "      <td>6.167</td>\n",
       "      <td>90.0</td>\n",
       "      <td>2.421</td>\n",
       "      <td>5.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>392.69</td>\n",
       "      <td>12.33</td>\n",
       "      <td>20.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>586</th>\n",
       "      <td>0.043</td>\n",
       "      <td>28.0</td>\n",
       "      <td>15.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.464</td>\n",
       "      <td>6.249</td>\n",
       "      <td>77.3</td>\n",
       "      <td>3.615</td>\n",
       "      <td>4.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>18.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>10.59</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>587</th>\n",
       "      <td>8.152</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.700</td>\n",
       "      <td>5.390</td>\n",
       "      <td>98.9</td>\n",
       "      <td>1.728</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>20.85</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>588</th>\n",
       "      <td>0.069</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.445</td>\n",
       "      <td>7.416</td>\n",
       "      <td>62.5</td>\n",
       "      <td>3.495</td>\n",
       "      <td>2.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>6.19</td>\n",
       "      <td>33.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>13.522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.631</td>\n",
       "      <td>3.863</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1.511</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>131.42</td>\n",
       "      <td>13.33</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>0.072</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.411</td>\n",
       "      <td>5.884</td>\n",
       "      <td>18.5</td>\n",
       "      <td>10.710</td>\n",
       "      <td>4.0</td>\n",
       "      <td>411.0</td>\n",
       "      <td>18.3</td>\n",
       "      <td>392.33</td>\n",
       "      <td>7.79</td>\n",
       "      <td>18.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>0.299</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.464</td>\n",
       "      <td>5.856</td>\n",
       "      <td>42.1</td>\n",
       "      <td>4.429</td>\n",
       "      <td>3.0</td>\n",
       "      <td>223.0</td>\n",
       "      <td>18.6</td>\n",
       "      <td>388.65</td>\n",
       "      <td>13.00</td>\n",
       "      <td>21.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>0.123</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.448</td>\n",
       "      <td>6.069</td>\n",
       "      <td>40.0</td>\n",
       "      <td>5.721</td>\n",
       "      <td>3.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>17.9</td>\n",
       "      <td>389.39</td>\n",
       "      <td>9.55</td>\n",
       "      <td>21.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>4.349</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.580</td>\n",
       "      <td>6.167</td>\n",
       "      <td>84.0</td>\n",
       "      <td>3.033</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>16.29</td>\n",
       "      <td>19.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.624</td>\n",
       "      <td>5.757</td>\n",
       "      <td>98.4</td>\n",
       "      <td>2.346</td>\n",
       "      <td>NaN</td>\n",
       "      <td>437.0</td>\n",
       "      <td>21.2</td>\n",
       "      <td>262.76</td>\n",
       "      <td>17.31</td>\n",
       "      <td>15.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>595</th>\n",
       "      <td>0.259</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.624</td>\n",
       "      <td>5.693</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.788</td>\n",
       "      <td>4.0</td>\n",
       "      <td>437.0</td>\n",
       "      <td>21.2</td>\n",
       "      <td>392.11</td>\n",
       "      <td>17.19</td>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>596</th>\n",
       "      <td>22.597</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.700</td>\n",
       "      <td>5.000</td>\n",
       "      <td>89.5</td>\n",
       "      <td>1.518</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>396.90</td>\n",
       "      <td>31.99</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>597</th>\n",
       "      <td>0.041</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4.86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.426</td>\n",
       "      <td>6.727</td>\n",
       "      <td>33.5</td>\n",
       "      <td>5.401</td>\n",
       "      <td>4.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.29</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>598</th>\n",
       "      <td>0.044</td>\n",
       "      <td>70.0</td>\n",
       "      <td>2.24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.400</td>\n",
       "      <td>6.871</td>\n",
       "      <td>47.4</td>\n",
       "      <td>7.828</td>\n",
       "      <td>5.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>14.8</td>\n",
       "      <td>390.86</td>\n",
       "      <td>6.07</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>599</th>\n",
       "      <td>6.539</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.631</td>\n",
       "      <td>7.016</td>\n",
       "      <td>97.5</td>\n",
       "      <td>1.202</td>\n",
       "      <td>24.0</td>\n",
       "      <td>666.0</td>\n",
       "      <td>20.2</td>\n",
       "      <td>392.05</td>\n",
       "      <td>2.96</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>0.040</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.52</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.404</td>\n",
       "      <td>7.287</td>\n",
       "      <td>34.1</td>\n",
       "      <td>7.309</td>\n",
       "      <td>2.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.08</td>\n",
       "      <td>33.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601</th>\n",
       "      <td>0.159</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.413</td>\n",
       "      <td>5.961</td>\n",
       "      <td>17.5</td>\n",
       "      <td>5.287</td>\n",
       "      <td>4.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>376.94</td>\n",
       "      <td>9.88</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>602</th>\n",
       "      <td>0.188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.448</td>\n",
       "      <td>5.786</td>\n",
       "      <td>33.3</td>\n",
       "      <td>5.100</td>\n",
       "      <td>3.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>17.9</td>\n",
       "      <td>396.90</td>\n",
       "      <td>14.15</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>0.331</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.507</td>\n",
       "      <td>8.247</td>\n",
       "      <td>70.4</td>\n",
       "      <td>3.652</td>\n",
       "      <td>8.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>378.95</td>\n",
       "      <td>3.95</td>\n",
       "      <td>48.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>604</th>\n",
       "      <td>0.054</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.92</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.437</td>\n",
       "      <td>6.549</td>\n",
       "      <td>51.0</td>\n",
       "      <td>5.960</td>\n",
       "      <td>4.0</td>\n",
       "      <td>289.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>392.85</td>\n",
       "      <td>7.39</td>\n",
       "      <td>27.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>0.045</td>\n",
       "      <td>25.0</td>\n",
       "      <td>4.86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.426</td>\n",
       "      <td>6.619</td>\n",
       "      <td>70.4</td>\n",
       "      <td>5.401</td>\n",
       "      <td>4.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>395.63</td>\n",
       "      <td>7.22</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       crim    zn  indus  chas    nox     rm    age     dis   rad    tax  ptratio       b  lstat  \\\n",
       "556   0.142   0.0  10.01   0.0  0.547  6.254   84.2   2.256   6.0  432.0     17.8  388.74  10.45   \n",
       "557   0.841   0.0   8.14   0.0  0.538  5.599   85.7   4.455   4.0  307.0     21.0  303.42  16.51   \n",
       "558   0.037  20.0   3.33   0.0  0.443  6.968   37.2   5.245   5.0  216.0     14.9  392.23   4.59   \n",
       "559   0.140  22.0   5.86   0.0  0.431  6.487   13.0   7.397   7.0  330.0     19.1  396.28   5.90   \n",
       "560   0.298   0.0   6.20   0.0  0.504  7.686   17.0   3.375   8.0  307.0     17.4  377.51   3.92   \n",
       "561   3.321   0.0  19.58   1.0  0.871  5.403  100.0   1.322   5.0  403.0     14.7  396.90  26.82   \n",
       "562   0.140   0.0   8.56   0.0  0.520  6.167   90.0   2.421   5.0  384.0     20.9  392.69  12.33   \n",
       "563   0.053   0.0   3.41   0.0  0.489  7.079   63.1   3.414   2.0  270.0     17.8  396.06   5.70   \n",
       "564   6.444   0.0  18.10   0.0  0.584  6.425   74.8   2.200  24.0  666.0     20.2   97.95  12.03   \n",
       "565   1.388   0.0   8.14   0.0  0.538  5.950   82.0   3.990   4.0  307.0     21.0  232.60  27.71   \n",
       "566   1.131   0.0   8.14   0.0  0.538  5.713   94.1   4.233   4.0  307.0     21.0  360.17  22.60   \n",
       "567   0.122   0.0   2.89   0.0  0.445  6.625   57.8   3.495   2.0  276.0     18.0  357.98   6.65   \n",
       "568   0.615   0.0   6.20   0.0  0.507  6.618   80.8   3.272   8.0  307.0     17.4  396.90   7.60   \n",
       "569   0.082  30.0   4.93   0.0  0.428  6.481   18.5   6.190   6.0  300.0     16.6  379.41   6.36   \n",
       "570     NaN   NaN  18.10   NaN  0.614  6.229    NaN   1.951   NaN  666.0     20.2  383.32  13.11   \n",
       "571   0.956   0.0   8.14   0.0  0.538  6.047   88.8   4.453   4.0  307.0     21.0  306.38  17.28   \n",
       "572   0.035  95.0   2.68   0.0  0.416  7.853   33.2   5.118   4.0  224.0     14.7  392.78   3.81   \n",
       "573   9.339   0.0  18.10   0.0  0.679  6.380   95.6   1.968  24.0  666.0     20.2   60.72  24.08   \n",
       "574   0.527   0.0   6.20   0.0  0.504  8.725   83.0   2.894   8.0  307.0     17.4  382.00   4.63   \n",
       "575   6.801   0.0  18.10   0.0  0.713  6.081   84.4   2.717  24.0  666.0     20.2  396.90  14.70   \n",
       "576   0.009  90.0   2.97   0.0  0.400  7.088   20.8   7.307   1.0  285.0     15.3  394.72   7.85   \n",
       "577   0.088  12.5   7.87   0.0  0.524  6.012   66.6   5.561   5.0  311.0     15.2  395.60  12.43   \n",
       "578   1.519   0.0  19.58   1.0  0.605  8.375   93.9   2.162   5.0  403.0     14.7  388.45   3.32   \n",
       "579   6.444   0.0  18.10   0.0  0.584  6.425   74.8   2.200  24.0  666.0     20.2   97.95  12.03   \n",
       "580   0.015  80.0   2.01   0.0  0.435  6.635   29.7   8.344   4.0  280.0     17.0  390.94   5.99   \n",
       "581   0.009  90.0   2.97   0.0  0.400  7.088   20.8   7.307   1.0  285.0     15.3  394.72   7.85   \n",
       "582   1.425   0.0  19.58   0.0  0.871  6.510  100.0   1.766   5.0  403.0     14.7  364.31   7.39   \n",
       "583   0.358   0.0   6.20   1.0  0.507  6.951   88.5   2.862   8.0  307.0     17.4  391.70   9.71   \n",
       "584   0.030  55.0   3.78   0.0  0.484  6.874   28.1   6.465   5.0  370.0     17.6  387.97   4.61   \n",
       "585   0.140   0.0   8.56   0.0  0.520  6.167   90.0   2.421   5.0  384.0     20.9  392.69  12.33   \n",
       "586   0.043  28.0  15.04   0.0  0.464  6.249   77.3   3.615   4.0  270.0     18.2  396.90  10.59   \n",
       "587   8.152   0.0  18.10   0.0  0.700  5.390   98.9   1.728  24.0  666.0     20.2  396.90  20.85   \n",
       "588   0.069   0.0   2.89   0.0  0.445  7.416   62.5   3.495   2.0  276.0     18.0  396.90   6.19   \n",
       "589  13.522   0.0  18.10   0.0  0.631  3.863  100.0   1.511  24.0  666.0     20.2  131.42  13.33   \n",
       "590   0.072  60.0   1.69   0.0  0.411  5.884   18.5  10.710   4.0  411.0     18.3  392.33   7.79   \n",
       "591   0.299  20.0   6.96   0.0  0.464  5.856   42.1   4.429   3.0  223.0     18.6  388.65  13.00   \n",
       "592   0.123   0.0   6.91   0.0  0.448  6.069   40.0   5.721   3.0  233.0     17.9  389.39   9.55   \n",
       "593   4.349   0.0  18.10   0.0  0.580  6.167   84.0   3.033  24.0  666.0     20.2  396.90  16.29   \n",
       "594     NaN   NaN  21.89   NaN  0.624  5.757   98.4   2.346   NaN  437.0     21.2  262.76  17.31   \n",
       "595   0.259   0.0  21.89   0.0  0.624  5.693   96.0   1.788   4.0  437.0     21.2  392.11  17.19   \n",
       "596  22.597   0.0  18.10   0.0  0.700  5.000   89.5   1.518  24.0  666.0     20.2  396.90  31.99   \n",
       "597   0.041  25.0   4.86   0.0  0.426  6.727   33.5   5.401   4.0  281.0     19.0  396.90   5.29   \n",
       "598   0.044  70.0   2.24   0.0  0.400  6.871   47.4   7.828   5.0  358.0     14.8  390.86   6.07   \n",
       "599   6.539   0.0  18.10   1.0  0.631  7.016   97.5   1.202  24.0  666.0     20.2  392.05   2.96   \n",
       "600   0.040  80.0   1.52   0.0  0.404  7.287   34.1   7.309   2.0  329.0     12.6  396.90   4.08   \n",
       "601   0.159   0.0  10.81   0.0  0.413  5.961   17.5   5.287   4.0  305.0     19.2  376.94   9.88   \n",
       "602   0.188   0.0   6.91   0.0  0.448  5.786   33.3   5.100   3.0  233.0     17.9  396.90  14.15   \n",
       "603   0.331   0.0   6.20   0.0  0.507  8.247   70.4   3.652   8.0  307.0     17.4  378.95   3.95   \n",
       "604   0.054   0.0  13.92   0.0  0.437  6.549   51.0   5.960   4.0  289.0     16.0  392.85   7.39   \n",
       "605   0.045  25.0   4.86   0.0  0.426  6.619   70.4   5.401   4.0  281.0     19.0  395.63   7.22   \n",
       "\n",
       "     medv  \n",
       "556  18.5  \n",
       "557  13.9  \n",
       "558  35.4  \n",
       "559  24.4  \n",
       "560  46.7  \n",
       "561  13.4  \n",
       "562  20.1  \n",
       "563  28.7  \n",
       "564  16.1  \n",
       "565  13.2  \n",
       "566  12.7  \n",
       "567  28.4  \n",
       "568  30.1  \n",
       "569  23.7  \n",
       "570  21.4  \n",
       "571  14.8  \n",
       "572  48.5  \n",
       "573   9.5  \n",
       "574  50.0  \n",
       "575  20.0  \n",
       "576  32.2  \n",
       "577  22.9  \n",
       "578  50.0  \n",
       "579  16.1  \n",
       "580  24.5  \n",
       "581  32.2  \n",
       "582  23.3  \n",
       "583  26.7  \n",
       "584  31.2  \n",
       "585  20.1  \n",
       "586  20.6  \n",
       "587  11.5  \n",
       "588  33.2  \n",
       "589  23.1  \n",
       "590  18.6  \n",
       "591  21.1  \n",
       "592  21.2  \n",
       "593  19.9  \n",
       "594  15.6  \n",
       "595  16.2  \n",
       "596   7.4  \n",
       "597  28.0  \n",
       "598  24.8  \n",
       "599  50.0  \n",
       "600  33.3  \n",
       "601  21.7  \n",
       "602  20.0  \n",
       "603  48.3  \n",
       "604  27.1  \n",
       "605  23.9  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_rows_count = data.shape[0]\n",
    "duplicated_rows_count = data[data.duplicated()].shape[0]\n",
    "print(\"% of duplicated rows to total rows in the dataset:\", duplicated_rows_count / total_rows_count * 100)\n",
    "print()\n",
    "\n",
    "labels = (\"Total rows:\", \"Duplicate rows\", \"Unique rows\")\n",
    "values = (total_rows_count, duplicated_rows_count, total_rows_count - duplicated_rows_count)\n",
    "plt.title(\"Dataset with duplicated rows\")\n",
    "plt.bar(labels, values)\n",
    "plt.show()\n",
    "\n",
    "data[data.duplicated()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparatory questions to ask"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do you know or have:\n",
    "\n",
    "- The domain knowledge needed to understand the data. Have you done your research ?\n",
    "- Where it comes from\n",
    "    - Is it manually/automatically generated data or mix of both?\n",
    "    - Process used to create the data\n",
    "- Do you know the nature of the bias in the data ? Does it need to be reduced and can it be ?\n",
    "- Do we know the strengths and weaknesses of the data ? Is the data trustworthy, dirty -> do we need to fix it ?\n",
    "    - Are there outliers ? should we keep them ?\n",
    "    - Are there missing data ? what should we do about them ?\n",
    "- Are the data representative of the domain ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5ZVFw4kaHVtO"
   },
   "source": [
    "### Please refer to the [Slides](http://bit.ly/do-you-know-your-data) for the step here after."
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Exploratory Data Analysis (Do we know our data).ipynb",
   "provenance": [],
   "version": "0.3.2"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
